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Taking into account the importance of principle of new information priority on grey system theory, a distinguishing method of buffer operators whether meet the principle of new information priority is put forward. It is proved that the popular strengthening buffer operator did not meet the principle of new information priority, but reflects the priority of old data by using the linear least squares perturbation theory. That is the newer data is perturbed, the smaller perturbation bound; the older data is perturbed, the larger perturbation bound under the equal perturbation. The usefulness of distinguishing method is validated by a real example. [ABSTRACT FROM AUTHOR]

The problem of seeking weights of decision-makers and attributes is studied in multi-attribute group decision making with interval grey numbers. For avoiding conflict between subjective weights and objective ones computed from attributes' values given by decision makers, the comprehensive weights are calculated by combining subjective weights and objective ones, where objective weights of attributes are obtained by using the maximum entropy model under the constrains of grey relation degree between the optimal project and every one. While, based on the degree of group consensus and information distribution, the weights of decision-makers are obtained by the maximum entropy thought and grey relation degree between every decision maker's comprehensive evaluations and average group evaluations. Finally, an aggregation approach of group decision making with interval grey numbers is presented. The numerical example is proved to verify the proposed method is more reasonable than other methods. [ABSTRACT FROM AUTHOR]

Why grey model is suitable for small sample is explained. Take discrete grey model as an example, based on matrix perturbation theory, we prove that the larger sample, the bigger perturbation bound and the smaller sample, the smaller perturbation bound under the equal perturbation when we use the traditional grey first order accumulate. The fractional order accumulate grey model is defined in order to reduce perturbation bound and its availability and practicality are verified by an example. [ABSTRACT FROM AUTHOR]

Aiming to reveal the changing law of modeling accuracy of grey Verhulst model resulted from the small perturbation of primitive sequence, we took the spectrum condition number of matrix as a tool of measuring the morbidity of this model and analyzed the value of conditions of coefficient matrix. The research result shows that only when the first data point of original data sequence be a constant (constant >0) and the rest of data points be all 0, this model will appear to be a serious morbid problem, however, at this time, it is meaningless to build a grey Verhulst model by using a raw data sequence with an inherent law for prediction. The research conclusion suggests that grey Verhulst model has no morbidity. [ABSTRACT FROM AUTHOR]

In order to accurately forecast pollutant emission volume nationwhide, this paper constructed an improved gray Markov chain model by combining gray prediction with Markov chain, given the fact that pollutant emission was under the influence of multiple gray factors and the acquired pollution data was characteristic of high stochastic volatility. This gray system model was used for predicting general trend of pollutant emission volume, while the Markov chain was used as a sensor for detecting the system's stochastic volatility. Moreover, this model improved through real-time correction for more accurate prediction. On that basis, this paper applied an improved model to forecast pollutants' emission reduction based on gray Markov chain. Finally, it carried out a case study to forecast SO2 emission volume nationwhide, which analysed the forecast accuracy and validity of this model. The results demonstrate that, compared with traditional ones, this newly-combined gray Markov model has improved the prediction accuracy obviously and is an effective algorithm for the prediction of pollutant emission volume. [ABSTRACT FROM AUTHOR]

A systematic carding on the research of grey incidence analysis modelling have been made in this paper. The grey incidence analysis models developed from the models based on incidence coefficient of each points in the sequences in early period to the generalized grey incidence analysis models which based on integral or overall perspective. From the grey incidence analysis models which measuring similarity based on nearness to the models which considering similarity and nearness respectively. The objects of the research advanced from the analysis of relationship among curves to that among curved surfaces, then forward to the analysis of relationship in three-dimensional space and even the relationship among super surfaces in n-dimensional space. The further problems remained to be studied in this field are clarified too. Several research approaches of grey incidence analysis modeling are clearly revealed. [ABSTRACT FROM AUTHOR]

For the stochastic multi-criteria decision-making problem, in which the information on criteria's weights is incomplete and the indices value of alternatives are in the form of intuitionistic fuzzy numbers, an intuitionistic random decision-making approach based on MYCIN certainty factor and prospect theory is proposed. According to the score function of intuitionistic fuzzy numbers and prospect theory, the MYCIN certainty factors of different alternatives in different indices are obtained. And the trust degrees of different indices are determined by using the grey incidence analysis. Then, the certainty factor fusion method in different indices is deduced to get the optimal alternative. It is proved that the fusion method satisfies the commutative law and the associative law. And the best alternative is got by using the method. Finally, an example shows the feasibility and validity of this method. [ABSTRACT FROM AUTHOR]

In order to improve the predictive accuracy of grey system prediction model with a stochastic oscillation sequence, this paper proposes an algorithm which can compress the amplitude and improve the smoothness of a stochastic oscillation sequence through a smoothness operator, and then deduces and establishes the prediction model of stochastic oscillation sequence. Through some examples' simulation, this paper compares simulation errors of this model with others; the results show that this novel method can evidently improve the simulative accuracy of stochastic oscillation sequence. [ABSTRACT FROM AUTHOR]

Due to the difficulty in obtaining information in the conceptual design phase, this paper presents a route airliner price forecast method based on I-GM(0,N) model for vacant point forecast in characteristic sequence. After selecting price-affecting factors as well as setting the Benchmark Ranking Series based on Grey Relational Analysis, the listing prices of X aircraft, a currently developed route airliner in China, is forecasted by I-GM(0,N). Proved to have good forecast and simulation results in a case study of X aircraft price forecast and price simulation of some current route airliners, this method is practical in price forecast of route airliners in conceptual design phase. [ABSTRACT FROM AUTHOR]

The hesitant fuzzy projection method is studied. The vectors of alternative, positive and negative ideal point are defined. A projection measure method is proposed, in which the attribute values are in the form of hesitant fuzzy set. A new relative closeness degree formula based on positive and negative ideal point is presented. By Jaynes' maximum entropy principle and alternatives' fair competition, a mathematical model is constructed to obtain the attribute weights. In the last, a numerical example is given to verify the effectivity and feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Gas pipeline is the bridge of connecting gas resource and market, and it realizes the approach of gas commercialization. Our country's gas pipeline network is developing with large-scale and integration, so we should establish an optimization model of natural gas pipeline net based on two algorithms to ensure pipeline net work safely, efficiently and economically. Based on the comparison of various existing optimization algorithms, the Improved Linear Approximation Method and Sequential Quadratic Programming Method (SQP) are selected as natural gas pipe network optimization algorithms. By analyzing the two algorithms' principle and aiming at the lowest energy consumption, while in order both to meet production needs and reduce algorithm's dependence on objective function and constraint conditions and ensure the efficiency and stability, we choose SQP to establish a universal steady-state operation optimization model which provides preliminary data analysis for software developers. [ABSTRACT FROM AUTHOR]

A flexible methodology is proposed to determine the aggregation of multi-stage linguistic information in an uncertain situation. More specifically, the frame of TOPSIS is designed to investigate the aggregation principle of multi-stage uncertain linguistic information, in which scheme performance in single stage can be calculated from a nearness perspective. Additionally, based on the decision matrix and Orness, a program is constructed to obtain the proper stage weights by minimizing the sum of deviation of the project nearness between adjacent stages in multi-periods, which concerns the comprehensive influence of both subjective preference and all the evaluation information. Furthermore, a model is constructed to evaluate the range of project nearness and study the risk problems in the process of multi-stage decision-making. Besides, another model is developed to examine the sensitivity of Orness parameter on the selection and ranking in multi-stage decision. Finally, a numerical case is conducted to show the above operations, which can demonstrate the feasibility and effectiveness of the new models and methods. [ABSTRACT FROM AUTHOR]

Aiming at the ill-conditioned problems in parameter identification of GM(1,1) power model, this paper first analyzes the measure method of the degree of morbidity of GM(1,1) power model based on the condition number of matrix inversion, then discusses the range of the condition number in three cases for different values of the background value and power index. On this basis, this paper summarizes the main factors which affect the morbidity of GM(1,1) power model and verifies the conclusions by an actual example. The results show that there is no morbidity in some cases. However, in some cases, the model is likely to be ill-conditioned. The background value and power index are main direct factors which affect the morbidity of GM(1,1) power model. [ABSTRACT FROM AUTHOR]

In view of limitation of the GM(1,1) model, constructed GM(1, 1, tα) model with time power using the theory of grey system modeling thought according to the practical application need. Studied this model's modeling process, parameter estimation, time response formula, and use the GM(1, 1, t²) model to forecast the embankment on soft ground of some coastal highway, high precision of the forecasting and fitting obtained in the application has proven this new model's effectiveness. [ABSTRACT FROM AUTHOR]

The convexity, concavity and the relative convexity of positive discrete series are denned, on this basis, the proximity of relative convexity among relevant factors is used to measure relation degree, we present the novel grey convex relation degree, the properties of the grey convex relation degree are discussed. We also put forward the independence from interference factors of the order of grey relations, and point out that the convex relation and other 6 kinds of grey relation degree satisfy the independence from interference factors, the grey relation degree put forward by Julong Deng could not satisfy the independence from interference factors. An example is given to illustrate that the grey convex relation degree can more really reflect the correlation degree among relevant factors sequences. [ABSTRACT FROM AUTHOR]

In this paper, the way of coupling in emergency has been studied in tackling issue on disaster derivative coupling in the GERTS network. Three kinds of notions about coupling have been put forward by having designed the logic structure of co-coupling nodes based on GERTS network, having defined co-coupling algorithm, and having studied the optimal evaluation of co-coupling algorithm parameters in different forms. This research provides the method for co-coupling analysis in the scenario of unconventional incidents and provides new outlook for the decision-making of "scenario-reaction" in unconventional incidents. [ABSTRACT FROM AUTHOR]