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In this paper, a decision-making system for precision marketing is presented to deal with real-world problems based on real e-business data collected in a company in Beijing. During the data preprocessing, the authors conducted a cleaning course to make sure the data to be analyzed in the latter part of the paper were credential. Based on the processed data, the authors analyzed consumer purchasing behaviors using three classic recommendation algorithms and made a performance comparison of the three algorithms. At the end of this paper, the authors proposed a series of precision marketing strategies which had been adopted by the data source company and had been proved to be effective in improving the performance. [ABSTRACT FROM AUTHOR]

Based on the PSR conceptual evaluation model of urban green and low-carbon development competitiveness, this paper evaluates the green and low-carbon development competitiveness of 13 cities in Beijing-Tianjin-Hebei from 2010 to 2019 and reveals their spatial effects and obstacle factors combined with the spatial autocorrelation and obstacle model. The results show the following: (1) In terms of the overall situation, the evaluation index of urban green and low-carbon development competitiveness in the Beijing-Tianjin-Hebei region shows a fluctuating upward trend as a whole from 2010 to 2019. Among them, the comprehensive evaluation indexes of Beijing, Zhangjiakou, and Tianjin are very competitive, while Hengshui, Handan, and Xingtai are relatively weak. (2) In terms of spatial data analysis, the global and local Moran's I of Beijing-Tianjin-Hebei cities from 2010 to 2019 were positive and passed the 1% significant level test. This shows that the comprehensive evaluation index of urban green low-carbon development competitiveness of Beijing-Tianjin-Hebei cities has a positive spatial correlation, and the spatial agglomeration effect is significant. On the whole, it presents a spatial agglomeration pattern of "high in the north, partial jump, and low in the south". (3) In the aspect of obstacle factor analysis, the proportion of the tertiary industry output value in GDP, energy consumption of ten thousand yuan of GDP, the urban green technology innovation level, and industrial soot emission of ten thousand yuan of GDP are the main obstacle factors restricting the improvement of urban green low-carbon development competitiveness in Beijing-Tianjin-Hebei cities. [ABSTRACT FROM AUTHOR]

Since the limitation of carbon emissions, China's photovoltaic (PV) industry has developed vigorously, while some traditional heavy industries have been violently hit. Therefore, the industrial production data exhibits significant nonlinear and complexity characteristics, which may affect prediction accuracy, thus hindering the corresponding department's decision-making. Consequently, a novel structure-adaptive fractional Bernoulli grey model is presented in this paper to surmount this toughie, and the core innovations can be summarized as follows. Initially, a novel time function term is utilized to depict the accumulative time effect, which can smoothly represent the dynamic variations and significantly strengthen the robustness of the new model. Besides, the fractional-order accumulation technique, which could effectively improve the predicting accuracy, is employed in the proposed model. Furthermore, the adaptability and generalizability of the proposed model can be enhanced by the self-adaptive parameters optimized by the Particle Swarm Optimization. For illustration and verification purposes, experiments on forecasting the annual output of Photovoltaic modules in China and the annual output of steel in Beijing are compared with a range of benchmarks, including the classic GM (1, 1), conventional econometric technology, and machine learning methods. And the results confirmed that the proposed model is superior to all benchmark models, which indicates that the novel model is indeed suitable for industrial production forecasting. [ABSTRACT FROM AUTHOR]

With the advent of the big data era, the use of computers has spread to all walks of life, and the finance and taxation industry is also in the middle of it. The current taxation system is huge and complex, and different tax types are inevitably linked to different economic indicators at a deep level, so tax forecasting requires personalised forecasting analysis for different tax types. This paper selects several tax types that account for a large proportion of tax revenue for prediction analysis, respectively, and conducts fusion research on multi-source big data, including business tax, corporate income tax, and personal income tax. Based on the multi-source big data fusion method, the prediction research on fiscal taxation tax types is conducted, and experiments are conducted with the taxation data of Beijing from 1995 to 2020 to predict the three tax types from 2017 to 2020. The results show that the deviation of the forecast data from the real tax data is small, controlling the forecast deviation to within 14%, indicating the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Public management service is the key to urban intelligent construction. This paper proposes an analysis method and model based on Spark big data framework and takes resident income, happiness index, urban planning, and ecological environment as the indicators of Spark big data. From the high difficulty of Spark big data cluster analysis of urban public management, we build the index weight by the entropy weight method, optimize the similarity calculation, and achieve the rapid understanding of urban public management. Subsequently, the Spark big data public management platform is applied to the public management of Beijing. The results indicate that the public management platform based on Spark big data framework can improve the public management level of the city and help to build an intelligent city. [ABSTRACT FROM AUTHOR]

In order to accurately divide the traffic control subarea and improve the regional coordination control effect, this paper studies the key technologies of traffic control subarea division from the influence of the discrete characteristics of the fleet on the coordinated control. Correlation analysis method and regression analysis method are used to construct the correlation model of adjacent intersections. The principle and process of transportation subarea division are designed by using analytic hierarchy process, and a new traffic subarea division model is proposed. Taking Gulou Street in Miyun District of Beijing as an example, combined with the green wave coordination optimization method, the new model was applied and simulated in SimTraffic. The simulation results show that the average delay of the intersection is reduced by 21.4%, the total number of stops is reduced by 9.62%, and the travel time is shortened by 8.75%. The new intersection degree model and the coordinated control scheme obtained by the traffic subarea division model make the highest traffic efficiency. That is, to verify the scientific research method of this paper, the research results are reliable and the practical application value is high. [ABSTRACT FROM AUTHOR]

Historic districts represent an important characteristic of Beijing and are also a crucial carrier of Chinese historic culture. However, they are significantly affected by the rapid urban constructions. Thus, it is of great significance to maintain and promote the public space in historic districts. This paper uses a multisource data superposition method to select the evaluation index of public space. The AHP was also used to complete the single-level and total-level ranking and calculation of evaluation indexes. Finally, based on the DEA model, a vitality evaluation model of Beijing historic district public spaces was developed and its validity was verified through a case study of the Wanping historic district. [ABSTRACT FROM AUTHOR]

The Beijing Winter Olympic Games is an extremely important event, and the supply of electricity is the basis for it. In order to prevent the sudden loss of power to the event, it is necessary to carry out power repair and restore normal power supply in the shortest possible time. Contemporary research is less focused on the emergency repair of power systems. This thesis studies the dispatching of power emergency materials in two stages and in the first stage, the minimum gap rate and the shortest time for material dispatching and transportation are mainly considered, and the required types of power emergency materials are dispatched from the storage near the Olympic venues to various power failure points. In the second stage, aiming at the shortage of power emergency materials at each fault point, the power emergency materials will be dispatched from the rear national power grid regional material reserve to the power emergency materials reserve near the Olympic venues and then dispatched to each power fault point through the power emergency materials reserve. Finally, this paper verifies the effectiveness of the combination of the primary and secondary dispatching models in an example, providing a reference for further improving the emergency response capability of the Olympic venues and improving the safety system of the power system. [ABSTRACT FROM AUTHOR]

Redevelopment of abandoned coal mine industrial sites (ACMISs) has been one of the critical research topics in recent years. The ecological system of ACMISs, which involves environmental, economic, and social characteristics, is an environment-economy-society (EES) composite system. Many factors with conflicting effects are involved in the sustainable development of this system. The matter-element analysis method presented in this paper can transform counteracting problems among influencing factors into compatible problems. This analytical approach leads to a reduction of the uncertainty of these influencing factors and provides a suitable research method to solve the complexity when selecting the most suitable reuse mode of the ACMIS. In this study, eight state-owned ACMISs in the suburbs of Beijing were investigated, and a suitability evaluation index system based on the EES conceptual framework was built. Targeting four reuse modes, including the residential area, the park, the scientific research and office campus, and the business district, we established a matter-element decision-making model to evaluate the priority of reuse mode selections scientifically. The results of our calculations show that the optimal reuse mode for the Qianjuntai, Muchengjian, and Huapogen ACMISs is the park; for the Da'anshan and Changgouyu ACMISs is the business district; for the Datai ACMIS is the scientific research and office campus; and for the Wangping ACMIS is the residential area. Since the suitability level of reusing the Anjiatan ACMIS in any of the four reuse modes is relatively low, it is recommended to reserve it for governmental strategically reserved open space. These real cases demonstrate that the research method is feasible and can be applied to reuse mode decisions for similar abandoned coal mines. [ABSTRACT FROM AUTHOR]

A novel two-axis solar tracker with parallel mechanism is proposed in this paper. A dynamic model is derived by using the virtual work principle and the consumed energy including the mechanical energy and motor energy loss is computed. Taking Beijing as the working location of the solar tracker, the energy consumptions of the parallel solar tracker and its corresponding serial solar tracker are compared based on the premise that the proposed solar tracker and its corresponding serial solar tracker have similar static stiffness. Mechanical energy consumption of the proposed tracker is reduced by 7.55% compared to the serial solar tracker. The motor energy loss of the parallel solar tracker is also significantly lower. This simple and low-energy consumption solar tracker is a good alternative to the traditional solar tracker with large energy consumption. [ABSTRACT FROM AUTHOR]

The normal supply of energy is related to the stable development of the economy and society. Forecasting energy consumption helps prepare for the normal supply of energy. In the study of energy consumption forecasting, different scholars have used different forecasting models. This paper uses five-year energy consumption data in the Beijing-Tianjin-Hebei region and uses the grey fractional FGM(1, 1) model to analyze the next six years. Then, the energy consumption of three places is predicted. The advantage of the grey score FGM(1, 1) model is that it can get more accurate prediction results based on a small amount of information. In this study, relatively outdated information affects the accuracy of prediction results. However, other prediction models have great limitations on data. Choosing the grey number fractional model for prediction research can get a more reasonable prediction result. We use the FGM(1, 1) model to make predictions and get the prediction results. In Beijing, the growth rate of natural gas consumption has slowed down and will be basically stable by 2023. The average annual deceleration of coal consumption is 32%. The average annual deceleration of coke consumption is 10%. Crude oil consumption decreased by 6.3% annually. Gasoline consumption is slowly increasing. The consumption of kerosene increased about 8% annually. Diesel consumption is slowly decreasing. Fuel oil consumption is reduced by 17% annually. The average annual growth rate of power consumption exceeds 6%. In Tianjin, the annual growth rate of natural gas consumption is about 5%. Coal consumption is reduced by about 8% every year. The average annual deceleration of coke consumption is 7%. Crude oil consumption decreased by 2.4% annually. Gasoline consumption is slowly decreasing. The consumption of kerosene has increased by about 20% annually. Diesel consumption is slowly decreasing. Fuel oil consumption is reduced by 20% annually. Electricity consumption is slowly increasing. In Hebei Province, the annual growth rate of natural gas consumption is about 15%. Annual coal consumption is reduced by about 3%. Coke consumption remained stable. Crude oil consumption is reduced by 3% annually. Gasoline consumption is slowly increasing, and kerosene consumption has increased by about 31% annually. Diesel consumption is reduced by about 3% annually. Fuel oil consumption remained stable. Electricity consumption is slowly increasing. [ABSTRACT FROM AUTHOR]

Reading comprehension Question-Answering (QA) for College Entrance Examination (Gaokao in Chinese) is a challenging AI task because it requires effective representation to capture complicated semantic relations between the question and answers. In this paper, a novel method of Chinese Automatic Question-Answering based on a graph is proposed. The method first uses the Chinese FrameNet and discourse topic (paragraph topic sentence and author's opinion sentence) to construct the affinity matrix between the question and candidate sentences and then employs the algorithm based on the graph to iteratively calculate the importance of each sentence. At last, the top 6 candidate answer sentences are selected based on the ranking scores. The recall on Beijing College Entrance Examination in the recent twelve years is 67.86%, which verifies the effectiveness of the method. [ABSTRACT FROM AUTHOR]

This paper studies a location-allocation problem to determine the selection of emergency shelters, medical centers, and distribution centers after the disaster. The evacuation of refugees and allocation of relief resources are also considered. A mixed-integer nonlinear multiobjective programming model is proposed to characterize the problem. The hierarchical demand of different refugees and the limitations of relief resources are considered in the model. We employ a combination of the simulated annealing (SA) algorithm and the particle swarm optimization (PSO) algorithm method to solve the complex model. To optimize the result of our proposed algorithm, we absorb the group search, crossover, and mutation operator of GA into SA. We conduct a case study in a district of Beijing in China to validate the proposed methodology. Some computational experiments are conducted to analyze the impact of different factors, such as the target weight setting, selection of candidate shelters, and quantity of relief resources. [ABSTRACT FROM AUTHOR]

With the rapid growth of car ownership, traffic congestion has become one of the most serious social problems. For us, accurate real-time travel time predictions are especially important for easing traffic congestion, enabling traffic control and management, and traffic guidance. In this paper, we propose a method to predict urban road travel time by combining XGBoost and LightGBM machine learning models. In order to obtain a relatively complete data set, we mine the GPS data of Beijing and combine them with the weather feature to consider the obtained 14 features as candidate features. By processing and analyzing the data set, we discussed in detail the correlation between each feature and the travel time and the importance of each feature in the model prediction results. Finally, the 10 important features screened by the LightGBM and XGBoost models were used as key features. We use the full feature set and the key feature set as input to the model to explore the effect of different feature combinations on the prediction accuracy of the model and then compare the prediction results of the proposed fusion model with a single model. The results show that the proposed fusion model has great advantages to urban travel time prediction. [ABSTRACT FROM AUTHOR]

Due to rapid urbanization and industrialization, atmospheric fine particulate matter (PM2.5) has become a primary urban pollutant, seriously affecting air quality and resident health. Existing airborne remote sensing and ground sensor monitoring can efficiently collect PM2.5 data. It is urgent yet challenging to fully use these two monitoring modes to analyze the spatial distribution and dynamic changes of PM2.5. This paper proposes a method to analyze the spatiotemporal characteristics of urban PM2.5 concentration using airborne and ground monitoring data. The method utilizes the boundary dimension and the radius dimension to describe the spatial distribution characteristics of PM2.5 and then adopts wavelet analysis to detect the fluctuation periods of PM2.5 concentration. Case study was performed based on the moderate-resolution imaging spectroradiometer (MODIS) data and the daily ground monitoring concentration of PM2.5 from 2014 to 2017 in Beijing. The decrease results of boundary dimension indicate that the changes in PM2.5 concentration tend to be slower over time, and the fluctuation amplitude gradually becomes smaller. The increase results closer to 2.0 in the radius dimensions suggest that the PM2.5 distribution becomes more uniform, indicating that the pollution control in Beijing had achieved initial success. The frequency results of wavelet analysis reveal that PM2.5 concentration in Beijing is mainly subject to periodic variation of 190 days. These findings can help us to gain deeper insight into the complex spatiotemporal characteristics of urban PM2.5. [ABSTRACT FROM AUTHOR]

The coordinated development of urban public infrastructure system and urban economic, social, and environmental system is an important goal for the integrated management and sustainable development of urban public infrastructure system. This paper constructs a research model of the degree of coupling coordination between urban public infrastructure system and urban economic, social, and environmental system using the analytic network process (ANP), the analytic hierarchy process (AHP), a combination evaluation method based on game theory, and a coupling coordination degree model. Using Beijing data from 2000 to 2016, the degree of coupling coordination between the Beijing urban public infrastructure system and the urban economic, social, and environmental system is empirically analyzed. This study finds that (1) the supply level of Beijing's urban public infrastructure system has an obvious impact on the degree of coupling coordination between the two systems. (2) The global financial crisis reduced the supply speed of the urban public infrastructure system in Beijing, and put the dynamic coupling state of the two systems in the low-level symbiosis stage. Beijing needs to improve the supply of urban public infrastructure to support the development of the urban economic, social, and environmental system. (3) Improving the supply level of the urban environmental infrastructure in Beijing, especially improving sewage disposal capacity and increasing the number of special vehicles for urban sanitation and the amount of domestic waste clearance, will positively affect the degree of coupling coordination between two systems. (4) An increase in the GDP of Beijing has a direct positive impact on the degree of coupling coordination. In addition, the increase in the social development level of the employees in three industries in Beijing has a significant impact on the degree of coupling coordination. [ABSTRACT FROM AUTHOR]

Beijing has an enormous transportation challenge: to relieve the extreme congestion that has arisen, largely due to overpopulation. To meet this challenge, the city administration has decided to extend its territory; a new city will be planned and built. This new city, Xiongan, will reduce the burden on the capital. A new high-speed railway (HSR) line is designed to transport millions of people every day within less than an hour. This study applies the potential of Geographical Information Systems (GIS) and multicriteria methods, Analytic Hierarchy Process (AHP) and Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE II), to determine the best alternative of transportation for the new high-speed railway line between Beijing and Xiongan, comparing different ones. The methodology consists of two stages. In the first stage remote sensing datasets such as ASTER DEM and LANDSAT images and GIS software such as ERDAS IMAGINE and ArcGIS have been used to determine settlement distribution, station location, elevation model, slope percentage, vegetation percentage, and route alignment for a new high-speed railway line for better understanding of its spatial distribution pattern over the study area. The second phase of the study focusing on assessing the various alternatives of transportation has been determined, and three approaches to choosing the best alternative have been introduced. In the paper we examine criteria associated with travel and economic criteria: travel time, the number of train stops, public satisfaction with transport, the number of seats per day, connectivity, operating costs, profit, and the payback period. Six alternatives of transportation have been studied. The stops in Guan and stations in the metro's rings have been investigated. In the second stage, the Analytic Hierarchy Process (AHP) and PROMETHEE II methods have been used to select the best alternative. The first approach uses only criteria related to the trip, as the criterion to choose the best alternative is the maximum of the net outranking flows by PROMETHEE II method; the second approach applies two independent criteria: the ratio of normalized operating costs and the normalized net outranking flows, and the ratio of the normalized payback period and the normalized net outranking flows; the third approach includes all defined criteria, and the criterion of choosing the best alternative is the maximum of net outranking flows as calculated by the PROMETHEE II method. The approaches have been analyzed with the purpose of comparing the results. The result indicates that it is expedient to have a station in Guan, which will increase the connection and connectivity among the cities while providing fast mobility options for a large number of inhabitants of Guan city. Furthermore, the result from Remote Sensing and GIS analysis demonstrates that the proposed high-speed railway line will be environmentally sustainable and is economically/socially feasible and that it will certainly attract current and future passengers because of their needs. [ABSTRACT FROM AUTHOR]

Current airspace is sectorized according to some predefined rules that are not flexible. To facilitate utilizing the airspace more efficiently, methods to design sectors need to be promoted. In this paper, we propose an undirected graph cut-based approach that employs a memetic local search-embedded constrained evolution algorithm, NSGA-II, to generate nondominated airspace configurations. We also propose a new concave hull-based method to automatically depict sector boundaries. In addition, we also study the configuration transition problem. We define the similarity of the two different configurations and calculate their similarity with a bisection diagram and a minimum cost flow algorithm. We build a forward network to represent configuration transitions across several consecutive time periods and use multiobjective dynamic programming to determine a series of nondominated configuration links from the first period to the end. We test our approaches by simulation in high-altitude airspace controlled by Beijing Area Control Center. The results show that our sectorization method outperforms the current configuration in practice, providing a lower sector number, lower intersector flow, more balanced workload distribution among the different sectors, and no constraint violations, so that the proposed approach shows its significant potential as practical applications for dynamic airspace configuration. [ABSTRACT FROM AUTHOR]