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Weaving and embroidering are the craft of weaving knitting or embroidering with cotton linen silk wool and other textile materials. China is the starting point of the Silk Road the birthplace of sericulture silk reeling and silk weaving and the exquisite skills of the weaving and embroidery industry enjoy a high reputation in the world. The patterns of woven and embroidered artifacts present historical cultural and artistic values highlight the formal beauty of plastic arts in traditional Chinese culture and provide rich material resources for cultural and creative design. However the traditional weaving and embroidering design mainly relies on manual pattern extraction which has problems such as high cost complicated steps long cycle and low efficiency. To this end this paper proposed an algorithm based on genetic algorithm to adaptively determine the optimal threshold value of Canny operator to automatically extract the patterns in the images of woven and embroidered artifacts improve the extraction efficiency and effect make the artifacts "live" and promote the inheritance and protection of traditional Chinese culture. To realize the automatic extraction of patterns from images of woven and embroidered artifacts and solve the problem that traditional Canny operators need to manually determine the threshold for edge detection of images of woven and embroidered artifacts and that the extraction efficiency is not high the article took the images of woven and embroidered artifacts as the research object proposing a genetic algorithm to optimize the Canny operator for the extraction of patterns from woven and embroidered artifacts. Firstly the paper analyzed the characteristics of the images of the woven and embroidered artifacts and used bilateral filtering algorithm and mean drift algorithm to smooth the noisy original image for the gray scale of the smoothed graph it selected the genetic algorithm to solve the optimal threshold of Canny operator and input the optimal threshold into Canny operator for the edge detection of the gray scale graph. Then the paper expanded the morphology of the edge image and automatically filtered out noise and incomplete pattern samples based on the area length and width of each connectivity domain. Finally the algorithm was evaluated for the effect of extracting patterns and the algorithm's running time. Experiments show that the algorithm can accurately detect the real edges of the pattern in the image of the woven and embroidered artifacts and the edges detected are clearer and more continuous than those detected by the other five traditional operators. In terms of pattern extraction precision and pixel accuracy PA it is better than the existing methods such as traditional Canny operators hybrid frog jump adaptive Canny operator Otsu maximum optimized Canny operator and so on. The algorithm is robust to the presence of folds that lead to pattern deformation in the woven and embroidered artifacts and all the patterns are successfully extracted. The algorithm can effectively detect the real edges of the patterns in the image of woven and embroidered artifacts and complete the pattern extraction. Woven and embroidered artifacts contain deep cultural heritage and artistic value and through pattern extraction designers can integrate traditional cultural elements into modern design to create unique cultural and creative products. In this paper the algorithm solves the problem that the traditional Canny operators need to determine the threshold value for the edge detection of woven and embroidered artifacts and that the extraction efficiency is not high. In the process of cultural and creative design the digitization of cultural and creative materials is the first step. In addition the grasp and application of the knowledge of history and culture artistic connotations unique stories and symbolic meanings embedded in patterns can more accurately capture the essence of the culture and the emotional expression it represents. For this reason it is of deeper significance and value to carry out research on the integration and mining of multimodal information such as patterns and knowledge in the future. [ABSTRACT FROM AUTHOR]

In order to overcome the existing exam management system on the speed and quality of test paper generating links exist defects, the coarse-grained parallel genetic algorithm combined with the adaptive technology, this paper proposed a fast parallel genetic algorithm of adaptive adjustment of population migration. Respectively from the examination of coding scheme, the optimization of genetic strategy, fitness function, crossover mutation operator selection and the selection of fitness value function, etc to carry on the design, had obtained the very good fitness, adopted the tactics of parallel at the same time, improved the running speed of the algorithm. Simulation experiment results show that the algorithm is successfully applied to the automatic group volume, volume and group to improve the efficiency and success rate are obvious, has the very good generality. The algorithm used in the intelligent fast automatic group volume is feasible and effective. [ABSTRACT FROM AUTHOR]

The problem of computing first edge server deployment is a fundamental problem in computing first network. In the actual scenario, the computing first edge server is close to computing power resources and provides access services for them to join the computing first network. However, the structure of computing resources is often determined by the actual demand, and changes with the change of demand. Under the constraint of computing first edge server resources, how to reasonably deploy computing first edge servers to ensure the effective construction of computing networks has become a hot topic of concern for all sectors. Firstly, this paper analyzed the deployment problem of computing first edge servers and transformed it into a multi-objective optimization problem with constraints. It proposed an improved genetic algorithm to address this issue. The advantages of this algorithm were as follows. It found non repetitive feasible solutions as the initial population provided more room for selection operations. When selecting, it adopted an individual balanced selection strategy to ensure the diversity and decentralization of the iterative population. When crossing and mutating, it adopted different types of random two point crossing and rotating random single point mutation strategies, thereby ensuring the diversity and diversity of the newborn population. The experiments is verified by resources deviation rate, load error rate, convergence rate. And expectation solution error rate shows that the algorithm is very effective and reasonable. [ABSTRACT FROM AUTHOR]

To address the issue of resource wastage and increasing latencies in the placement process of edge servers, this paper analyzed and modeled the user density and average access time of edge server placement schemes as multi-objective optimization problems. It designed an edge server placement scheme based on user density and average access time, and proposed a multi-objective sea-horse genetic algorithm (MOSGA) to solve this problem. The MOSGA algorithm firstly used the idea of multi-objective optimization algorithm to improve the SHO algorithm, so that the SHO algorithm could be applied to multi-objective optimization problems. It used the genetic algorithm to improve the propagation operation of the SHO algorithm, so that the MOSGA could better jump out of the local optimal solution and accelerate the solution of the problem. The proposed algorithm was verified on the data set of Shanghai Telecom, and the simulation experiment results show that MOSGA is obviously better than RA, K-means, NSGA and LMM, which not only effectively solves the problem of server resource waste, but also greatly reduces the time of terminal equipment to access the server. [ABSTRACT FROM AUTHOR]

In the dynamic network environment, real-time video transmission based on streaming protocols will encounter a large number of packet loss issues. This paper proposed an adaptive forward error correction code method based on GA-BP neural network. This method recovered lost data packets by designing adaptive forward error correction codes. Firstly, the paper designed a frame level forward error correction framework, which mainly includes video codec, RS forward error correction codec module, and forward error correction code redundancy calculation module, to simulate the general video transmission environment; Then, the paper designed the GA-BP model and applied it to the redundancy calculation of RS-FEC to achieve a frame level unequal protection scheme; Finally, based on GE channel simulation network, it generated packet loss data, trained offline model, and conducted experimental verification. The experiments results show that compared to StaticRS and DeepRS, this method can recover lost data packets more efficiently with lower redundancy, resulting in higher quality video. [ABSTRACT FROM AUTHOR]

In this paper, the intrinsic structure model of SiCp/Al composites was constructed based on the analysis of static and dynamic mechanical properties of SiCp/Al composites. Quasi-static tensile tests were conducted for SiCp/2a14Al composites with 20% volume fraction using an electronic universal testing machine to study the static mechanical properties of the material. Dynamic compression tests were conducted at different temperatures (20 °C-400 °C) and strain rates (500 /s-3000 /s) using a Hopkinson compression bar test to analyze the dynamic mechanical properties of the material. The Johnson-Cook (JC) intrinsic structure model of SiCp/Al composites was constructed based on the material stress-strain test data under static and dynamic conditions, and the model was optimized by genetic algorithm. The results show that the SiCp/Al composites exhibit a strain-reinforcement effect under quasi-static conditions; under dynamic loading conditions, the material flow stress increases with the strain rate and exhibits a strain-rate reinforcement effect, which is related to the volume fraction of silicon carbide particles. With the increase of temperature, the flow stress decreases and exhibits a temperature-softening effect. The average error between the least squares fitted JC model and the experimental values is large, and the model error is reduced after optimization by genetic algorithm, which can accurately predict the rheological behavior of SiCp/2a14Al composites. [ABSTRACT FROM AUTHOR]

Objectives: Global navigation satellite system (GNSS) coordinate time series provide important data support for the study of crustal movement and deformation, and plate tectonics. Due to the noise caused by various external factors, the GNSS coordinate time series cannot reflect the real motion information of the station well. To effectively reduce the noise in the GNSS time series, we adopted a noise-reduction method combining genetic algorithm (GA) and variational mode decomposition (VMD-GA-VMD). Methods: First, the genetic algorithm was used to optimize VMD parameters, and the envelope entropy of the input signal was used as the fitness function of the genetic algorithm to find the optimal VMD parameter combination suitable for the signal. According to the optimized parameters, the signal was decomposed by VMD to obtain a series of modal components. Then we calculated the multi-scale permutation entropy (MPE) of each component and then regarded the MPE as the criterion of the noise component. Finally, according to the MPE, the noise components were identified and removed, and the remaining components were reconstructed to obtain the noise-reduced signal. In this paper, the noise reduction effect of GAVMD was analyzed through the example of noise reduction of analog signal and observation data, and compared with wavelet denoising (WD) and empirical mode decomposition (EMD) methods. Results: The experiment results show that: (1) The noise reduction results from the analog signals show that WD and EMD have the incomplete and excessive troubles on the noise reduction, respectively. However, GA-VMD can effectively eliminate noise and retain effective signals. From the evaluation index, compared with WD and EMD, the signal-to-noise ratio were increased by 5.18 dB and 2.91 dB, the correlation coefficient by 0.05 and 0.02, respectively, when using GA-VMD. (2) For the complex observation, we used the noise and velocity uncertainty as accuracy indicators to evaluate the noise reduction effects of the three methods. The results show that WD can only extract a part of the white noise, while EMD and GA-VMD can completely remove the white noise. GA-VMD can reduce the flicker noise to the range of 0 to 6 mm/a0.25. For the velocity uncertainty, the average gain rates of GA-VMD relative to the WD and EMD are 69% and 15.33%, respectively. GA-VMD has an average correction rate of 79.89% and 84.46% for the velocity uncertainty and flicker noise of GNSS coordinate time series. Conclusions: Therefore, GA-VMD is the most effective one among the three noise reduction methods, which can effectively reduce the noise in the GNSS time series and improve its accuracy. However, in this paper, we only discussed the effect of GA on VMD parameter optimization without comparing it with other methods. Hence, it will be the key for studying the advantages and shortcomings of those optimization algorithms in the selection of VMD, and improving the accuracy on the GNSS time series in the future. [ABSTRACT FROM AUTHOR]

The traditional express terminal distribution mode has problems such as redundant construction of express outlets and overlapping delivery paths, and the joint distribution model can effectively solve these problems. Therefore, this paper studies the location path of express terminal outlets in the case of simultaneous receiving and dispatching and uncertain receiving demand under the joint distribution model. Firstly, a two-stage mathematical optimization model is established to deal with the problem of uncertain receipt volume by introducing random chance constraints. Secondly, a hybrid heuristic algorithm based on genetic algorithm and adaptive large neighborhood search algorithm is designed. Finally, numerical experiments show that the designed hybrid algorithm has a faster convergence speed and better solution quality than the traditional genetic algorithm. Too high or low risk acceptance of the optimization scheme in the random demand environment will lead to the increase of cost. With the increase of the ratio of customer receiving and dispatching volume, the cost of express terminal distribution first decreases and then increases, The nearest outlet return strategy can effectively reduce the distribution cost of enterprises. [ABSTRACT FROM AUTHOR]

Aiming at the problems of low efficiency of minor repair and maintenance of military equipment in the synthetic force, strong randomness of maintenance human resource allocation, and unbalanced and unreasonable resource utilization, taking the armored equipment as the research object, this paper analyzes the task and demand of the operation process of relying on maintenance workshops to carry out equipment minor repairs in peacetime. The optimization goals are to minimize the total maintenance period and maximize the balance of maintenance personnel allocation, taking the professional and quantity requirements of maintenance personnel in the maintenance process as constraints, a mathematical model of the equipment minor repair operation process is constructed. And then aiming at the sequence relationship of maintenance procedures, a maintenance network process update algorithm with tabu table and a genetic algorithm considering equipment parallel maintenance operations are proposed to optimize the maintenance human resource allocation strategy for equipment minor maintenance operations. The example shows that the algorithm is reasonable and feasible. [ABSTRACT FROM AUTHOR]

Aiming at the problems of low efficiency and unstable solutions of traditional genetic algorithm (GA) in solving traveling salesman problem (TSP), this paper proposed a novel genetic algorithm based on genes pool (GPGA). GPGA searched for edges that decreased the fitness of Hamiltonian cycles from the population and constituted a gene pool as excellent genes. The parent generation reproduced the better offspring of Hamiltonian cycles under the guidance of the gene pool. The gene pool also synchronously updated according to the better Hamiltonian cycles and helped the current Hamiltonian cycles evolve to the optimal Hamiltonian cycle step by step. The computational results demonstrate that GPGA is better than traditional genetic algorithm and several improved genetic algorithms under the same preconditions. [ABSTRACT FROM AUTHOR]

Ride-sharing is an effective way to solve traffic congestion. However, passengers’ lack of trust in ride-sharing behavior is a problem that affects the development of ride-sharing. To solve this problem, by introducing trust weight and user preferences to measure by the trust level, taking the shortest total driving distance of the vehicle and the highest total trust value as the objective function, and considering the vehicle loading capacity constraints, vehicle travel distance constraints, passenger demand response constraints and vehicle station service constraints, this paper constructed a ride-sharing model considering passenger trust degree, and used an improved genetic algorithm to solve the model. Finally, this paper used the data of operating vehicles in the surrounding areas of Beijing Xinfa to verify the algorithm. The results show that the model can effectively reduce the total vehicle distance while ensuring a high level of passenger ride-sharing trust. The distance cost is 14.8% less than the model only considering distance optimization, and the trust level is 3.3 times higher. This paper verified the effectiveness of the model and the algorithm through the comparative analysis of the optimization results. [ABSTRACT FROM AUTHOR]

Assessing the sustainable development of agriculture is a hot topic in global agricultural research and an important task of rural revitalization and agricultural upgrading in the new era. Reform and opening up promote the rapid development of the agricultural economy, but the conflict between agricultural development and agricultural resources and ecological environment is serious. Since the 18th National Congress of the CPC, the sustainable development of agriculture has been given more prominence. It is of great significance to study the evaluation of agricultural sustainable development. Firstly, this paper studies the relevant literature on agricultural sustainable development evaluation at home and abroad. Based on wavelet transform, support vector machine(SVM), genetic algorithm (GA)and ant colony optimization(ACO) algorithm, a combination evaluation method of wavelet and intelligent optimization support vector machine is proposed. Secondly, by referring to the existing evaluation index system and combining with the actual situation of China's agricultural development, the alternative index set of agricultural sustainable development evaluation is established. Using SPSS software, the significance and correlation of 150 primary indexes are analyzed, and an evaluation index system including 62 indexes is established. Thirdly, using one-dimensional discrete stationary wavelet analysis, data denoising processing, genetic algorithm, ant colony algorithm, optimize the parameters of support vector machine, get better penalty parameters, kernel function, insensitivity coefficient, and then train the support vector machine. Fourth, taking 31 provinces (municipalities) in China as an example, this paper evaluates the agricultural sustainable development by applying the wavelet-GASVM model and the wavelet-ACOSVM model, and using the GA-SVM model and the ACO-SVM model to evaluate the agricultural sustainable development of 31 provinces (municipalities) in China. Fifthly, the reliability of the wavelet intelligent optimization SVM method is verified by changing the number of test sets and conducting multiple tests. The evaluation and simulation results show that: 1) The mean square error of agricultural sustainable development evaluation of Wavelte-GASVM is 9.641×10-5, and the correlation coefficient is 0.980; however, under the same training set and test set, the mean square error and correlation coefficient obtained by GASVM are 0.006 and 0.979, respectively. 2)The mean square error of Wavelet-ACOSVM agricultural sustainable development evaluation was 9.318×10-5, and the correlation coefficient was 0.972; the mean square error MSE and correlation coefficient of ACO-SVM are 0.016 and 0.953, respectively, under the same training set and test set. 3) Change the number of test sets and perform several tests and compare the results of GASVM model and ACO-SVM model before and after wavelet denoising respectively. It can be seen that under the GASVM model, the mean square error of the running results after wavelet denoising is smaller than that before wavelet denoising, and the correlation coefficient is larger than that before wavelet denoising, and the running time is shorter. Under the ACOSVM model, the mean square error of the running result after wavelet denoising is also smaller than that before wavelet denoising, and the correlation coefficient is larger than that before wavelet denoising, and the running time is shorter. Conclusion: The prediction accuracy and convergence speed of agricultural sustainable development evaluation by wavelet-GASVM and wavelet-ACOSVM are better than GA-SVM and ACO-SVM, respectively, and the effect of agricultural sustainable development evaluation by wavelet-GASVM is more ideal. This study provides a method reference for agricultural sustainable development assessment. [ABSTRACT FROM AUTHOR]

Aiming at the problem of production imbalance caused by experience-based equipment purchase strategy in hybrid flow shop, this paper proposed a barrel-greedy algorithm. Under the constraint of fixed equipment cost, this algorithm took the fastest production cycle of the production line as the goal, and used the short board idea of barrel effect to identify the bottleneck process, and on this basis, it introduced the greedy idea for the inconsistent characteristics of the bottleneck processes of multiple products in the production line. Then, comparing the solution results of different algorithms based on the actual production line case, the barrel-greedy algorithm has certain advantages in solving quality and efficiency compared with exhaustive search algorithm and improved genetic algorithm. Finally, taking the actual production line as the background, this paper used Plant Simulation to compare the production line before and after transformation, and verifies the feasibility and effectiveness of the algorithm in practical production. [ABSTRACT FROM AUTHOR]

In this paper, the theoretical innovation is made on the traditional fire distribution problem. Considering the actual situation of the ship’s fault, based on the principle of multi-objective optimization, the improved distributed genetic algorithm is used for preliminary solution. And the corresponding fault-tolerant control law is formulated to correct the fault-tolerant strategy, so as to ensure the better fire strike effect and maintain a high fault tolerance. Finally, through simulation experiments, it is verified that this method can converge to the optimal solution quickly, and can reduce the loss to the maximum extent when compensating. It has certain research value for combat. [ABSTRACT FROM AUTHOR]

Mission Planning of Border Control operations refers to the process in which the relevant forces of border control make use of the Mission Planning system to plan and design relevant actions in order to achieve a specific action destination, so as to form a relatively scientific and reasonable action plan. In this paper, strategic analysis is carried out from the subject object, system composition and hierarchy of border control action task planning, and based on the transmission algorithm, the basic process of border control action task planning is discussed. [ABSTRACT FROM AUTHOR]

For the material supply planning of warship formation under constraint conditions. this paper designs the optimization objective function of the planning model, based on the operation and penalty time cost of unmanned aerial vehicles (UAVs), ship supply time window. maximum load capacity of UAV and other constraints. In order to solve the problem that adaptive genetic algorithm (AGA) is prone to fall into local optimum, a nonlinear probability function is designed to determine the crossover probability and mutation probability. Further more a UAV material supply planning based on nonlinear adaptive genetic algorithm (NLAGA) is proposed. The experimental results show that the NLAGA method is superior to AGA and the improved AGA method in solving the Solomen problem of the standard calculation example. Under the condition of optimal supply time and cost, NLAGA method can effectively determine the number of UAVs and flight path planning in the material supply task of the warship formation. [ABSTRACT FROM AUTHOR]

Aiming at the rescheduling problems of hybrid flow shop with rush order insertion, this paper proposed a hyper-heuristic genetic algorithm based on the two-layer coding. Aiming at the double-decision characteristics of order sort and machine selection in the hybrid flow shop, this algorithm designed a two-layer coding scheme in the low level. Each individual represented both order sort and machine selection information, and corresponded to a unique scheduling solution. Then the low level proposed 12 kinds of sorting and selection heuristics for iterative optimization of individuals. The high level of the algorithm used an adaptive genetic algorithm to determine the operation combination of order sort heuristic and machine selection heuristic and the sort of execution of each combination. And it designed an adaptive mutation operator to optimize the effectiveness of the algorithm. The results of large-scale data experiments show that the proposed algorithm has good solving quality and efficiency. [ABSTRACT FROM AUTHOR]

With the continuous growth of vehicle ownership and the popularization of Internet of Vehicles applications， vehicle terminals generate large amounts of data messages that need to be processed in real time. In the scene of high-speed vehicle movement， the traditional Internet of Vehicles navigation system has a transmission delay due to vehicle differential positioning data， which results in a certain deviation in vehicle positioning results and cannot obtain high-precision positioning results in time. Based on this， this paper proposes a technology solution for car networking navigation based on BDS positioning and edge computing. It uses an improved genetic algorithm to allocate resources for terminal positioning requests， effectively reduces the service delay of the entire edge network， and uses optimize the lossless Kalman filter algorithm based on edge node to improve the positioning accuracy of the car network node. Experiments show that the method proposed in this paper can provide real-time accurate， low-latency and high-precision positioning services for large-scale Internet of Vehicles terminals， and has high practical application value. [ABSTRACT FROM AUTHOR]

As Software Defined Network（SDN） is increasingly widely used in various scenarios, a new challenge for SDN to support dynamic requirements of various applications begin to emerge. Digital Twin（DT） can enhance the capabilities of SDN in aspects of real-time analysis, deduction, and network control, and consequently satisfy the dynamic requirements of various applications. Whereas, current DT constructing schemes for SDN usually suffer from the challenges of strict delay constraint, heavy computing overhead, and low cooperating efficiency. To address the above issue, this paper proposes a novel Variable Granularity-Digital Twin（VGDT） according to the application requirement and available computing resource. Based on the distribution characteristic of the computing resource in the network, VGDT builds a cooperatively optimizing model to ensure the delay and effectiveness of the DT for SDN. Then, this paper proposes a hybrid coding genetic algorithm to solve this model, which can achieve the best granularity and the DT placement policy. The simulation results show the performance of VGDT. Compared with current DT, VGDT has higher integrity and validity of digital twin model under limited computing resource. [ABSTRACT FROM AUTHOR]

In order to solve the problem that the driver is difficult to monitor and input complex during the running process, this paper proposed and implemented a driver fuzzing tool DrgenFuzzer based on the fitness and input constraint model. The tool utilized the kernel tracing technology combined with the static analysis of binary programs to realize the information monitoring of the driver operation, analyzed the driver interface parameters, designed a sample constraint scheme, proposed a new fitness calculation scheme and a crossover mutation scheme. Experiments show that compared with the commonly used kernel fuzzing tools, the test success rate of samples generated by this tool after the input constraint model is more than 10 times that of other tools, and the quality of the generated samples is higher. This tool performed a fuzzy test on the driver and exploits the null pointer reference vulnerability in the i2c driver. DrgenFuzzer can effectively guide and standardize sample generation, improve the success rate and operating efficiency of sample testing, and enhance the vulnerability mining ability. [ABSTRACT FROM AUTHOR]

In view of the lack of effective optimization design theory based on structural performance for cable dome structures, a quantitative evaluation method of structural reliability based on nonlinear characteristics of cable domes from the perspective of reliability was proposed, and the influence law of element cross section on structural reliability was analyzed through a Geiger-type cable dome structure model. On this basis, genetic algorithm was used to explore the section optimization design method based on structural reliability without increasing the structural quality. Following this, a cable layout optimization scheme was proposed based on the optimization concept that aims to enhance structural redundancy. Finally, the section optimization design of the cable dome structure under the new cable layout scheme was performed to identify the structural form and quality layout with the most reliable performance. The research revealed that the variations of cross sections of different types of elements had generated different effects on structural reliability. The structural reliability was enhanced from 0.728 123 to 0.891 355 with an optimization rate of 22.4% on the condition that the structural quality should not be increased. Meantime, the structural reliability was improved from 0.728 123 to 0.862 487 with an optimization rate of 18.5% with the cable layout optimization scheme. The further optimization of the section was performed on the aforementioned basis, and the overall structural reliability was further improved from 0.862 487 to 0.997 676 with an optimization rate of 15.7%. Therefore, the reliability-based nonlinear reliability evaluation method, section optimization and cable layout optimization design of cable dome structure proposed in this paper had significant theoretical research and engineering application value. [ABSTRACT FROM AUTHOR]

Considering that the traditional simultaneous pickup and delivery mode is single and cannot cope with the complex and changeable reality needs, this paper proposed VRPD-SPD. Firstly, the method used a hybrid integer linear programming model to minimize the total cost between vehicles and drones. Secondly, the algorithm made a TSHAG algorithm. In the first stage, the greedy algorithm combined with the saving algorithm to generate the initial solution. In the second stage, in order to optimize initial solution, the solving process used improved genetic algorithm, which constructed the multivariate encoding mode to boost the decoding efficiency, improved the crossover operator to increase the search space of the neighborhood solution, and designed a new mutation operator to improve the global optimization performance of the algorithm. Finally, the experimental results show that the proposed TSHAG algorithm can solve VRPD-SPD problem effectively. [ABSTRACT FROM AUTHOR]

In order to carry out the correction work of traffic simulation model more efficiently, this paper proposed a model correction framework based on parameter sensitivity analysis . The method simplified the model by exploring the key parameters that affected the model accuracy through sensitivity analysis, and corrected the model with the usage of the calibrated key parameters. To justify this, the paper analyzed the car following model and lane changing model under the simulation condition of urban expressway weaving area. Firstly, it obtained the value of model parameters under different traffic flow levels through a large number of simulation experiments. Secondly, this paper formulated the interval division rules and cross combination rules of model parameters to improve LH-OAT algorithm and genetic algorithm (GA) . Then, it used the improved LH-OAT algorithm (ILH-OAT ) and GA algorithm to analyze the sensitivity of the model parameters and used GA to calibrate the key parameters. Finally, this paper checked the error of the simulation results according to the verification index. The results show that the combination of ILH-OAT and GA simplifies the simulation model and reduces the simulation operation cost. Besides, it also adds verisimilitude to the simulation on reflecting real traffic operation. [ABSTRACT FROM AUTHOR]

The sorting operation of the production line in mechanical manufacturing has the double complexity of the problem and data. To optimize the sorting operation and improve production efficiency, this paper designed a method for data representation and an evolutionary algorithm based on population optimization. At the same time, this paper arranged and disclosed a real industrial data set. The method for data representation abstracted the original job data by referring to the bag-of-words model. The evolutionary algorithm used deep reinforcement learning to initialize the population in the genetic algorithm and introduced the elite retention strategy, which improved the optimization ability of the algorithm. Finally, it compared the proposed algorithm with other algorithms on the real industrial data set and travelling salesman problem data set. The results show that the proposed algorithm can find a better sorting sequence and the access path, which verifies the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

In order to meet the diversified travel demand of passengers and plan the tourism transportation network, this paper puts forward the perspective of passenger intermodal transport, a new road and short-haul general aviation transportation intermodal (road-air intermodal) mode was proposed. A bilevel programming model of road-air intermodal tourism transportation network was constructed. The upper layer mode aims at the shortest total travel time of passengers and total operating cost of the traffic network to designed the traffic route scheme. The lower layer model aimed at the shortest travel time of individual passenger and allocates passenger flow to the route. The proposed model was solved by genetic algorithm, and the example analysis shows that the road-air intermodal transportation network model is scientific, reasonable and feasible. [ABSTRACT FROM AUTHOR]

In view of the lack of effective optimization design theory based on structural performance for cable dome structures, a quantitative evaluation method of structural reliability based on nonlinear characteristics of cable domes from the perspective of reliability was proposed, and the influence law of element cross section on structural reliability was analyzed through a Geiger-type cable dome structure model. On this basis, genetic algorithm was used to explore the section optimization design method based on structural reliability without increasing the structural quality. Following this, a cable layout optimization scheme was proposed based on the optimization concept that aims to enhance structural redundancy. Finally, the section optimization design of the cable dome structure under the new cable layout scheme was performed to identify the structural form and quality layout with the most reliable performance. The research revealed that the variations of cross sections of different types of elements had generated different effects on structural reliability. The structural reliability was enhanced from 0.728 123 to 0.891 355 with an optimization rate of 22.4% on the condition that the structural quality should not be increased. Meantime, the structural reliability was improved from 0.728 123 to 0.862 487 with an optimization rate of 18.5% with the cable layout optimization scheme. The further optimization of the section was performed on the aforementioned basis, and the overall structural reliability was further improved from 0.862 487 to 0.997 676 with an optimization rate of 15.7%. Therefore, the reliability-based nonlinear reliability evaluation method, section optimization and cable layout optimization design of cable dome structure proposed in this paper had significant theoretical research and engineering application value. [ABSTRACT FROM AUTHOR]

The mean volumetric diameter (MVD) and liquid water content (LWC) are two important parameters that affect aircraft icing, but they are difficult to be measured accurately in practice. If these two parameters can be accurately obtained in real time, they can provide some guidance for icing prediction and the establishment of aircraft airworthiness certification standards. In this paper, a prediction model of icing meteorological parameters based on the genetic‑algorithm‑optimized neural network is proposed. We use the ice thickness and icing rate of different combinations of measuring points, ambient temperature, flight speed and wing angle of attack as input parameters, and the icing meteorological parameters MVD and LWC as output parameters, and develop a prediction model of icing meteorological parameters optimized by the genetic algorithm, This model predicts the icing meteorological parameters of the numerical calculation test group data and the icing wind tunnel experiment data. The results show that the relative error of the prediction model for numerical calculation of icing meteorological parameters of the test group is within 10%, and the relative error of the experiment data is within 20%. This method is feasible. [ABSTRACT FROM AUTHOR]

In the context of distributed energy grid integration, time-of-use electricity prices are widely used, and fluctuations in user response load will inevitably affect the stability of the grid and cause the increase in active power loss of the distribution network. Optimal operation model of the power grid. The user load response model is established based on the time-of-use electricity price, and the distribution network operation optimization model is constructed with the user’s daily electricity cost and the minimum distribution network loss as the objective function. The evaluation function method is used to convert multiple goals into single goals. The genetic algorithm introduces the simulated annealing Metropolis criterion to optimize the charging and discharging strategy of the user-side energy storage. The simulation results prove that the strategy proposed in this paper can effectively reduce the power loss of the distribution network and the cost of user electricity, and at the same time, it is verified that the algorithm proposed has the advantages of fast optimization speed and good convergence performance. [ABSTRACT FROM AUTHOR]

At present, it is difficult to evaluate the feasibility of the current reservoir dam emergency plan and lack of technical guidance in the evaluation process. From the four dimensions of organization system, operation mechanism, emergency support and emergency training, this paper established the secondary feasibility evaluation index system of reservoir and dam emergency plan. It used analytic hierarchy process and entropy weight method to calculate the principal and objective solid weight of each index and introduced genetic algorithm and variable weight theory to make coupling correction. Combined with cloud model theory, a comprehensive evaluation model for the feasibility of reservoir dam emergency plan was established. The results show that the comprehensive score of the feasibility of the reservoir emergency plan is 85.66, and the evaluation grade is excellent, which is consistent with the evaluation result of the plan. The validity and applicability of the improved method in the feasibility evaluation of reservoir dam emergency plan are verified. [ABSTRACT FROM AUTHOR]

In this paper, the finite element simulation software COMSOL is used to calculate the band-gap of the two-dimensional chiral phononic crystal, and the influence of the scatterer parameters and ligament coating parameters on the bandgap is analyzed. On this basis, the effective parameter design space for the optimal design of the band-gap of chiral phononic crystals is determined; then, based on the ISIGHT optimization design platform, the genetic algorithm is embedded to carry out the optimal design of the band-gap of two-dimensional chiral phononic crystals. In the optimal design process of the bandgap, the effective configuration parameters of the two-dimensional chiral phononic crystal are used as the design variables, and the maximum relative band-gap width is the goal to design the unit cell configuration of the chiral phononic crystal. Then, the optimized unit cell configuration is used as the initial configuration, the effective material parameters of the chiral phononic crystal are used as the design variables, and the maximum relative band-gap width is the goal to further realize the optimal design of the band-gap of the two-dimensional chiral phononic crystal. This work maximizes the potential of optimal design of the band-gap of two-dimensional chiral phononic crystals, and provides a reliable and effective analysis and design method for giving full play to the role of chiral phononic crystals in vibration and noise reduction. [ABSTRACT FROM AUTHOR]

Resource allocation is an important part of equipment maintenance support. In order to optimize resource allocation reasonably after equipment failure, quickly repair the equipment failure and restore the battle effectiveness of the army, in this paper, a task-oriented equipment maintenance support resource allocation model is proposed and solved by the genetic algorithm. The algorithm adopts the real number coding form which is closer to the problem space. Through embedding the random substitution module with limited selection, it solves the problem of task and resource allocation under the condition of clear task requirement and maintenance resource, and avoids the repeated allocation of resource. This paper proves the feasibility, validity and applicability of the method through the analysis of concrete examples, and provides a train of thought for the design and development of this kind of decision support system, as well as an important reference for the equipment maintenance resource support decision-making in the future information battlefield. [ABSTRACT FROM AUTHOR]

This paper proposed the Non-cooperative Game Theory-based of load-reduction Master Controller Reselection model in Software Defined Networking to address the multi-controller load imbalance problem, called GTMCR. To begin with, the discriminating overload controller utilized the Overload Dynamic Thresholds approach (ODT). Next, the migration of switches followed a Priority Decision Switching Strategy (PDSS). Finally, the constructed optimization model took the load balancing degree of controller clusters, average total delay and switch migration cost as utility functions. To prevent the global optimal solution from slipping into the local optimum, the solution value of optimal deployment used the Genetic Algorithm for Improved Multi-objective Optimization (GAIMO) with the addition of a similarity operator to boost the algorithm’s convergence speed and the accuracy of the global optimal solution. The experimental results show that this mechanism effectively balances the control plane load while achieving the goal of optimizing network performance. [ABSTRACT FROM AUTHOR]

There are similarities between the growth processes of ingot crystalline silicon with different sizes, so the growth law of small size crystals could be transferred to large size crystals. In this paper, transfer learning (TL) was used to design the hot zone of the G8 ingot furnace. The design targeted parameters are the positions and volumes of the side and top heaters, and the height of the partition block on the side insulation cage. The main design goals are to reduce the dislocation defects inside the crystal, suppress polycrystalline at the edge of the silicon ingot and make the solid-liquid interface slightly convex. First, a neural network was used to establish a mapping model between the hot zone geometric parameters and hot zone evaluation parameters for the existing G7 ingot furnace. Then the model was transferred to the G8 ingot furnace. The effects of different model structures on the transfer process were analyzed. Then Dropout was used to determine whether the model is overfitting. The genetic algorithm (GA) and the clustering algorithm (CA) were applied to optimize the hot zone geometric parameters. The above is the process of G8 hot zone design. Finally, the numerical simulation method was used to study the temperature distribution and solid-liquid interface shape of the optimized schemes. The final selected scheme could achieve high quality crystal growth. Then the scheme was applied to the hot zones of G7 and G8 furnaces. The results show that the axial temperature gradient of G8 in silicon melt and silicon crystal is smaller than that of G7, and the radial temperature gradient at the solid-liquid interface is also smaller than that of G7. It is beneficial to reduce the thermal stress inside the crystal. [ABSTRACT FROM AUTHOR]

The selection of build orientation in 3 D printing is one of the key factors that affect processing quality. Aiming at the current algorithm only with consideration of the optimization on the premise of equal thickness layering, this paper proposed a build orientation optimization algorithm in terms of an adaptive layered model. Firstly, this paper analyzed the surface accuracy of products under different build orientation in combination with the characteristics of 3 D printing layer by layer, and established a build orientation dependent optimization function to minimize volume error. Then, it employed the genetic algorithm to search the optimal solution in the global scope to determine optimal build orientation through steps such as STL model rotation transformation and ad aptive layering. Finally, this paper conducted the comparison between proposed and published algorithm. The experimental results show that the proposed algorithm can further reduce the volume error and improve the surface quality. [ABSTRACT FROM AUTHOR]

For the problem of the master-slave game of the garbage sorting center with the harmful waste sorting task, this paper proposed a two-level planning and site selection scheme with the upper reward mechanism. Firstly, it constructed the up - per model with the collection point and harmful waste recycling logistics enterprises as the initiator, and constructed a lower model with the sorting center and the recycling point as receivers. Secondly, the upper and lower layers all introduced the environmental infringement costs brought about by the existence of harmful garbage and considered the reward level as the decision-making scheme to interrelate the cost of the upper and lower layers. Finally, it solved the model examples by genetic algorithm. By comparison with a single layer dual target model, this paper discussed the advantages and disadvantages of the twolayer cost model on cost control. [ABSTRACT FROM AUTHOR]

In order to improve the learning effect in e-learning system and recommend learning resources to learners to meet their personalized needs, this paper constructs a max-product fuzzy relation equation, which links learners’ learning behavior, learning state and characteristics of learning resources. In the process of finding learning resources that match learners’ learning state, a fuzzy relation programming is constructed, and an unconstrained genetic algorithm is designed to solve it. Experimental results show the effectiveness of the algorithm. The conclusion effectively improves the matching degree between learning resources and learning needs, which is suitable for e-learning systems in different learning scenarios. The algorithm proposed in this paper is also suitable for other problems that need to solve the max-product fuzzy relation equations. [ABSTRACT FROM AUTHOR]

In order to improve the practicability and accuracy of the optimal configuration of the integrated energy system, this paper proposes a two-stage multi-objective optimal configuration method for integrated energy system. In the first stage, the optimal type and capacity of the equipment, and also units combination can be obtained by designing the objective function that minimizes the economic cost and the carbon dioxide emissions during a life cycle. In the second stage, the objective function is formulated to obtain the optimal daily operating cost, and the branch operating method is proposed to solve the optimization problem. Finally, a residential area in the north is used as an example for simulation. The simulation results show that the optimal configuration method proposed in this paper has obvious advantages over traditional methods in terms of economic and environmental benefits. The method can effectively achieve collaborative optimization, and has higher practicality and accuracy. [ABSTRACT FROM AUTHOR]

CAN( controller area network) bus is the most widely used field bus. Due to the lack of authentication and message checking mechanism, CAN bus has great security risks, so it is necessary to design a defense mechanism for CAN bus. In this paper, a priority hopping mechanism is designed, which introduces the dynamic hopping of identifiers by Hash function into a real-time scheduling algorithm. The fixed priority is calculated by a genetic algorithm, and the compromise range of priority is found out. Each frame is grouped, and the ID segment of data frame is segmented and reconstructed. The former part of the ID segment determines the priority and performs priority hopping, while the latter part of the ID segment hops dynamically at one time. Experimental results show that using dynamic priority and one-time ID Hopping to hop has a greater security improvement than the existing ID Hopping mechanism. [ABSTRACT FROM AUTHOR]

Bus is a "quasi-public" product that provides services for citizens to travel and reflects the management level of a city.Research on reasonably planning bus dispatch plays a critical role in the maintenance of bus normal operation.Aiming at the problems of public bus passenger flow being easily affected by the weather and the large difference in passenger flow and its degree of change in different ti me periods, a multi-objective genetic algorithm based on the "platykurtosis-peak" factor was proposed in this paper in order to optimize urban bus dispatching.The model is composed of three stages.First,platykurtosis and peak were defined in the article through passenger flow data, whose rationality has been verified. Secondly, the smallest passenger travel cost reflected by the waiting time of passengers at the station and the smallest public transportation operating cost represented by the cost of all aspects of the bus are used to establish the bus dispatching optimization model.Finally,the "platy kurtosis-peak" is integrated into the chromosome gene sequence so that the optimal bus dispatch plan can be continuously iteratively worked out by the multi-objective genetic algorithm. The test results show that compared with the traditional algorithm, the optimized model based on "platy kurtosis-peak" reduces the passenger travel cost by 13. 75 % and the operating cost of public transportation by 1. 7 %, which is better than the traditional algorithm as well as proving the effectiveness of it for optimizing bus dispatching. [ABSTRACT FROM AUTHOR]

Gas-phase reactions are reliable strategies to explore the stability and activity of metal clusters, which can provide the information of products and the cluster activities by comparing the changes of the X, Y-axis of the mass spectrum before and after the reaction.Combined with ab initio calculation, we can deeply explore the structure of clusters, reaction intermediates and final products, explore the reaction thermodynamics and kinetic process,and reveal the essence and relationship between cluster structure,stability and reaction activity.In this paper,by investigating the gas-phase reaction mass spectra of Cun--clusters with NO and O2,,Agn- clusters with O2,and further combined with the ab initio calculation,novel open shell superatoms Cu18-,double closed shell superatoms Ag17- with unique stability are reported.Besides,we demonstrated the donation and back donation interactions between NO and Cun--.Chemisorption of O2 on Cu-2n+1,Cu-2n+1(or Ag-2n) clusters follows the double and single electron transfer mechanism, respectively.Among them, the behavior of O2 on Cu;;-is enabled by the spin conservation rule.By analogizing the cluster and O2 as base and acid respectively, we found a phenomenon that clusters with different alkalis pass through different degrees of spin excitation or dissociation barriers,and finally release almost the same heat for O2 dissociation. Based on this, a fully new mechanism of O2 on metal clusters was proposed: leveling effect of spin accommodation.Calculations of energy decomposition analysis-natural orbitals for chemical valence show that the activities of Cu; clusters towards NO and O2,Ag; clusters toward O2 are closely related to cluster geometry, electronic shell arrangement and energetics data. [ABSTRACT FROM AUTHOR]

This paper proposed a bit-plane encryption algorithm using noise adaptive embedding for noisy images such as radar and remote sensing images. Firstly, the algorithm adaptively found the best embedding threshold in different noisy images using genetic algorithm, and used an encryption algorithm that did not require a secret key at higher noise values to cross-embed two pieces of secret information into the first and in the three-dimensional plane. Then it used the BBE algorithm to compress the flag bit data to the second bit plane. Finally, it used the same encryption algorithm to embed the remaining secret information into the second and fourth bit planes to complete information hiding at the second bit plane redundancy. Experimental analysis shows that under the condition of satisfying high-capacity embedding, compared with other adaptive bit-plane steganography algorithms, it has better concealment and stronger robustness, and at the same time, it can resist the current better steganalysis algorithms to ensure security of data transmission. [ABSTRACT FROM AUTHOR]

In this paper, the elastic modulus and creep degree of RCC gravity damwere calculated based on the measured displacement and strain. Using Fortran language and numerical calculation software Flac3D, a creep numerical calculation program was developed to realize the simulation calculation of the whole process during construction and operation. The displacement and strain measurements during the sudden rise of water level were used to invert the stable elastic modulus of the dam body and dam foundation. Based on the orthogonal experiment design and the creep numerical calculation program, a sample of the correspondence between the parameters to be inverted and the calculated strain values at the monitoring points was obtained. With the help of intelligent algorithm support vector machine (SVM) and genetic algorithm (GA), the calculated strain values and GA-SVM prediction model for inverse parameter relationship was established. During the inversion calculation, the measured strain value at the monitoring point was true, and the calculated strain value was directly calculated by the GA-SVM prediction model, eliminating the need for numerical calculation. The strain values calculated according to the feedback of the inversion parameters were in good agreement with the measured values. The research results show that the inversion calculation method of the creep variant in this paper is reasonable and effective, which greatly reduces the numerical calculation of the entire process of the creep variant and its parameter inversion time required. [ABSTRACT FROM AUTHOR]

This paper proposed and discussed a genetic algorithm based on virtual machine migration model in cloud data centers called GA-VMM. It took into account several important parameters to frame the objective function for the virtual machine migration which overwhelmed the old strategies and thus it made the virtual machine migration more reasonable and fair. It constructed the mathematics model of power consumption and live migration cost of virtual machine in GA-VMM. It designed a global optimization genetic algorithm for how virtual machine migrated and placed. Using a corporation cloud data centers servers, this paper did some simulation experiments. The experimental results show that GA-VMM can effectively reduce the number of physical machine usages and virtual machines migrations compared with the common strategy. It had also obtained the fewer SLA violation and low energy consumption of data centers in our test. [ABSTRACT FROM AUTHOR]

In view of the uncertainty of demand and return for perishable products in different periods, this paper proposed a multi-period model of closed-loop logistics network for perishable products and the corresponding mixed integer linear programming ( MILP) model, so as to achieve the decision of the minimum total system cost, the best facility location and vehicle route. In order to avoid the influence of uncertain parameters effectively, it converted some defined constraints in the model to robust corresponding expressions by using cardinality constrained robust approach. Through the case of the fruit and vegetable agricultural enterprises of Shanghai, this paper verified the validity of model by genetic algorithm. The result shows that compared with the single period system, the multi-period system has the advantages of dynamic performance and lower system cost. Meanwhile, it verifies the feasibility and effectiveness of the robust model through the analysis of the variation of uncertain budget parameters. It provides a reference for the construction of multi-period closed-loop logistics network and the reduction of system cost under uncertain environment. [ABSTRACT FROM AUTHOR]

Traditional runtimes based on user estimating is usually less accurate. This paper combined the categorization with the instance-based learning method, used the template similarity and numerical similarity method to find the similar jobs of the current jobs in historical data, and used historical scheduling data to predict the runtimes of the current jobs. This paper only took seven job attributes into account, which included user name, group name, queue name, application name, requested number of processors, requested runtime, requested memory. It applied genetic algorithm to train the best parameters, and used similar jobs attributes to predict runtimes. Compared with the existing method, experimental results show that the proposed prediction method achieves a similar underestimate rate on the premise of using fewer parameters, and gets a lower mean absolute error. Moreover, on the HPC2N04 and HPC2N05 datasets, the mean absolute errors reduce 43% and 77% respectively. This paper studied the effect of using online prediction to replace user estimation on job scheduling, analyzed the results and pointed out the future improvement directions. [ABSTRACT FROM AUTHOR]

Effective ecological network construction can guarantee regional ecological security, which is an important path to achieve regional sustainable development. Based on the analysis of the connotation of ecological nodes, this paper establishes a multi- level ecological node identification system based on "resource- based strategic point - structural strategic point - structural weak point", and uses remote sensing images, land use data, POI data, etc. of Jintan district in 2015. This paper also employs multi- target genetic algorithm, minimum resistance model and so on. The hierarchical ecological network in the ideal state of Jintan district was constructed, and the ecological network was quantitatively evaluated by using indexes such as the network topology and nodes utility. Based on the above, the following main conclusions were obtained: (1) Multi- level ecological network is significantly better than the general network in terms of nodes utility and overall network performance. And the water network area has a strong applicability. (2) As the current situation of the ecological network distribution is uneven, the ecological nodes' layout needs to be optimized. The optimized node coverage increased by 17.70%, the uniformity of node distribution decreased by 45.45%, and the average clustering coefficient increased by 87.36%. (3) Multi-level ecological node system has practical application, and different management strategies should be adopted for different types of ecological nodes. [ABSTRACT FROM AUTHOR]

This paper aims at the problem of ammunition scheduling strategies. The differences of demand for time and security among different forces are considered in the case of a fight. The multi⁃objective problem is measured by the game theory，and then the ammunition scheduling strategy is optimized by the genetic algorithm. The simulation results show that the game theory constructed in this paper can more rationally optimize the ammunition scheduling strategies with different demand in different cases. [ABSTRACT FROM AUTHOR]

Mutually exclusive products (such as liquids, hazardous chemicals, etc.) cannot be mixed into the same container. Logistics companies usually use multi-compartment trucks to deliver mutually exclusive products to customers. The loading and vehicle routing strategies are the key issues to determine the distribution efficiency and distribution costs. Considering the constraints of loading and unloading sequence and transportation time of mutually exclusive products, a joint optimization model of loading and distribution is constructed to minimize the distribution cost. This paper designs an improved genetic algorithm for solving the model, using the queen evolution and the edge reconstruction crossover operations based on probability to lift the ability of finding the optimal solution. Then we construct the testing examples based on the vehicle routing problem benchmark provided by Augerat to verify the running time and solving efficient of genetic algorithm. The simulation results show that, the solutions obtained by improved genetic algorithm are better than those of classical genetic algorithm, for small-scale examples, the improved genetic algorithm can obtains global optimal solution; for the medium-sized or large size examples with no more than 101 customers, the approximate optimal solution can be obtained in 130 seconds using genetic algorithm. The innovation of this paper lies in the establishment of a mathematical model for a new expended vehicle routing problem and the design of a fast and effective algorithm for solving the model. The mathematical model and algorithm of this paper provide a theoretical basis and algorithmic support for logistics companies to draw up distribution schedule of mutually exclusive products. [ABSTRACT FROM AUTHOR]

Aimed at the problem that the genetic algorithm is slow in convergence and easy to fall into the local optimal solution in the process of function optimization, this paper proposed a genetic algorithm called DIAGA with semi-initialization and probability perturbation strategy. Firstly, it introduced the probabilistic perturbation strategy to increase the population diversity in the late iteration of the algorithm, and used the semi-initialization fundamentally to change the limitation of the algorithm in the comparison process of the global optimal solution. Then this paper used the Markov chain theory to prove the convergence of DIAGA. Finally, it performed simulation experiments on six standard test functions. Simulation results show that the DIAGA algorithm is more effective in getting rid of local convergence and has more obvious advantages in search accuracy and convergence speed. For multidimensional test functions, the optimization accuracy has increased by about 29% . [ABSTRACT FROM AUTHOR]

Due to the relatively low long-period amplitude values and its simplex form of attenuation, the normative design response spectrum cannot effectively response to the long-period ground motion characteristics, therefore, it is very significant to adopt a reasonable design response spectrum model to reflect the long-period ground motion response spectrum. In order to solve this problem, this paper takes the long-period ground motion of Taiwan Chi-chi Earthquake in 1999 as an example, firstly, divides it into groups according to ground acceleration, site classification and anti-seismic design sectionalization, and makes a contrastive analysis compared with the normative design response spectrum; secondly, based on the characteristics of long-period acceleration response spectrum, a design response spectrum suitable for long-period ground motions is proposed, at the same time, its advantages and disadvantages are contrasted with those of conventional design response spectrum. The research shows that the long-period design response spectrum proposed in this paper has better applicabilities; the genetic algorithm is used to fit the long-period ground motion response spectrum one by one and the corresponding spectral parameter suggested values are given, what’s more, the long-period ground motions collected in the Weihe Basin of Wenchuan Earthquake in 2008 are used to verify the reasonability of the spectral parameter suggested values, which provide a reference for the revision of the normative design response spectrum. [ABSTRACT FROM AUTHOR]