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维普期刊数据库

Air target intention recognition and causal effect analysis combining uncertainty information reasoning and potential outcome framework

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Chinese Journal of Aeronautics 2024年第1期37卷 287-299页

作者： Yu ZHANG Fanghui HUANG xinyang deng Mingda LI Wen JIANG School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710129China

Recognizing target intent is crucial for making decisions on the ***,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent recognition *** with the challenge,a target intention causal analysis paradigm is proposed by combining with an Intervention Retrieval(IR)model and a Hybrid Intention Recognition(HIR)*** target data acquired by the sensors are modelled as Basic Probability Assignments(BPAs)based on evidence theory to create uncertain ***,the HIR model is utilized to recognize intent for a tested sample from uncertain ***,the intervention operator under the evidence structure is utilized to perform attribute intervention on the tested *** retrieval is performed in the sample database based on the IR model to generate the intention distribution of the pseudo-intervention samples to analyze the causal effects of individual sample *** simulation results demonstrate that our framework successfully identifies the target intention under the evidence structure and goes further to analyze the causal impact of sample attributes on the target intention.

关键词： Causal effect analysis Hybrid intention recognition Intervention retrieval Target intention Uncertainty reasoning

维普期刊数据库

Controlling underestimation bias in reinforcement learning via minmax operation

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Chinese Journal of Aeronautics 2024年第7期37卷 406-417页

作者： Fanghui HUANG Yixin HE Yu ZHANG xinyang deng Wen JIANG School of Electronics and Information Northwestern Polytechnical UniversityXi’an 710129China College of Information Science and Engineering Jiaxing UniversityJiaxing 314001China

Obtaining the accurate value estimation and reducing the estimation bias are the key issues in reinforcement ***,current methods that address the overestimation problem tend to introduce underestimation,which face a challenge of precise decision-making in many *** address this issue,we conduct a theoretical analysis of the underestimation bias and propose the minmax operation,which allow for flexible control of the estimation ***,we select the maximum value of each action from multiple parallel state-action networks to create a new state-action value ***,a minimum value is selected to obtain more accurate value ***,based on the minmax operation,we propose two novel algorithms by combining Deep Q-Network(DQN)and Double DQN(DDQN),named minmax-DQN and ***,we conduct theoretical analyses of the estimation bias and variance caused by our proposed minmax operation,which show that this operation significantly improves both underestimation and overestimation biases and leads to the unbiased ***,the variance is also reduced,which is helpful to improve the network training ***,we conduct numerous comparative experiments in various environments,which empirically demonstrate the superiority of our method.

关键词： Reinforcement learning Minmax operation Estimation bias Underestimation bias Variance

维普期刊数据库

A Novel Method for Discrete Evidence Fusion Based on Dijkstra Shortest Path Algorithm

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A Novel Method for Discrete Evidence Fusion Based on Dijkstr...

第32届中国控制与决策会议

作者： Bo Liu Yang Yang xinyang deng Science and Technology on Avionics Integration Laboratory School of Electronics and Information Northwestern Polytechnical University

Discrete evidence generally exists in the fields of expert systems,pattern recognition,and decision *** to solve the fusion of discrete evidence is an open *** order to solve the problem that the number of calculations increases exponentially with the increase of the number of discrete evidences,a method for calculating the shortest path based on Dijkstra is ***,the normalized discrete evidence is decomposed into the exact value of the evidence as far as possible,and then the Jousselme distance between the two pairs of evidence between the evidence groups is *** Jousselme distance is designed to measure the conflict between the *** the Dijkstra shortest path algorithm is used to find the path with the largest and smallest Jousselme *** path here indicates the discrete evidence group with the largest fusion distance and smallest fusion *** use Dempster combination to fuse the evidence after weighted average and give the interval value of ***,two groups discrete evidence are given for verification to illustrate the rationality and effectiveness of the method.

关键词： Discrete evidence Dijkstra algorithm Jousselme distance Dempster combination

A satisfaction degree of D numbers and its application in multi-criteria decision making

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A satisfaction degree of D numbers and its application in mu...

第32届中国控制与决策会议

作者： Bo Liu Yebi Cui xinyang deng Science and Technology on Avionics Integration Laboratory School of Electronics and Information Northwestern Polytechnical University

The introduction of uncertainty theory into the field of decision making provides a solution for the processing of qualitative *** the field of uncertain information decision making,there are many widely used theoretical methods,such as D-S evidence theory and D number ***,Yager proposed a method for evaluating the satisfaction of belief structure based on uncertain target values based on D-S evidence ***,there is no related research on satisfaction evaluation in D number *** this paper,combined with fuzzy set theory,a calculation method of D numbers satisfaction is *** the element correlation,the decision information is effectively processed by generating a correlation fuzzy membership *** application example of a manufacturing company selecting a supplier illustrates the effectiveness of the calculation method in this paper.

关键词： D numbers Dempster-Shafer belief structure Belief structure satisfaction

A method to extend TOPSIS for decision-making problems with interval weight

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A method to extend TOPSIS for decision-making problems with ...

第30届中国控制与决策会议

作者： Weiwei Hu xinyang deng Wen Jiang School of Electronics and Information Northwestern Polytechnical University

In some cases, determining precisely the exact value of the weight is difficult and their values are considered as interval numbers. Therefore, in this paper, we extend the TOPSIS method for solving multiple attribute decisionmaking problems with interval weight. Firstly, the evaluation on each alternative and the weight of attribute are given as interval numbers. Then, based on the proposed interval t-norm, the original interval decision matrix and interval weight are merged into interval weighted decision matrix. Next, the ranking result of the alternatives is obtained by TOPSIS method. Finally, an example is given to highlight the procedure of the proposed method.

关键词： Interval numbers Interval t-norm Interval weight TOPSIS Multiple criteria decision making

A new method to air target threat evaluation based on Dempster-Shafer evidence theory

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A new method to air target threat evaluation based on Dempst...

第30届中国控制与决策会议

作者： Haibin Liu Zeyu Ma xinyang deng Wen Jiang School of Electronics and Information Northwestern Polytechnical University

As a core problem for air defense decision-making, air target threat evaluation has a great strategic significance because an accurate and reasonable evaluation result of air target threat can significantly improve the combat efficiency especially in the multiobjective environment. However with many new weapons appearing, the battlefield situation is becoming more and more complex and *** this paper, a new method for air target threat evaluation based on Dempster-Shafer evidence theory is proposed. The method use trapezoidal fuzzy number to obtain the every target’ threat degree which can be seen as an evidence. And the weight of each evidence is derived by simultaneously considering its uncertainty（*** entropy of evidence） and correlation with other evidences（i.e. the correlation coefficient with other evidences）. The value of air target threat evaluation is obtained by D-S evidence theory. Finally, an illustrative example and a comparison with another approach are given to show the effectiveness of the proposed approach.

关键词： Air Target Threat Evaluation Trapezoidal Fuzzy Number deng Entropy Corrrelation Coefficient of Evidence Dempster-Shafer Evidence Theory

An Improved Approach for Adversarial Decision Making under Uncertainty based on Simultaneous Game

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An Improved Approach for Adversarial Decision Making under U...

第30届中国控制与决策会议

作者： Zeyu Ma Shiyu Wang xinyang deng Wen Jiang School of Electronics and Information Northwestern Polytechnical University

Game theory is used widely when to make decisions in an adversarial environment. There are usually two adversarial players in a game and both of players try to maximize their payoffs. However the classical game assumes the players are rational and do not consider other uncertainty factors such as personal preference. This paper proposes a method to take uncertainty into account when using game theory to make decisions. And Dempster-Shafer evidence theory is used to deal with the uncertainty, then the payoff matrix of game can be modified properly and the new payoff matrix reflects the impact of uncertain factors. Finally the equilibrium solution is computed which is the optimal decision under uncertainty.

关键词： Decision Making Game Theory Evidence Theory Uncertainty

Multi-attribute Decision-making Method Based on Interval-valued Intuitionistic Fuzzy Sets and D-S Theory of Evidence

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Multi-attribute Decision-making Method Based on Interval-val...

第24届中国控制与决策会议

作者： Juan Liu, xinyang deng, Daijun Wei, Ya Li and Yong deng School of Computer and Information Sciences, Southwest University,400715 Chongqing, China

The theory of interval-valued intuitionistic fussy sets is now widely studied to deal with vagueness and D-S theory of evidence has a widespread use in multi-attribute decision-making （MADM） problems under uncertain situation. In this paper, A new method based on interval-valued intu- itionistic fuzzy sets and D-S theory of evidence is proposed to handle MADM problems. In our method, the interval- valued intuitionistic fuzzy numbers are represented by the interval average numbers. These average numbers are assigned to corresponding basic probability assignment （bpa） based on discounting method. Then the D-S combination rule is used to fuse information in order to obtain final mass functions for each alternative, thus the order of each alternative is obtained. A numerical example is used to illustrate the efficiency of the proposed method.

关键词： Interval-valued intuitionistic fuzzy sets D-S theory of evidence Multi-attribute decision-making Interval average number Data fusion

THE COMBINATION PREDICTION OF TRANSMEMBRANE REGIONS BASED ON DEMPSTER-SHAFER THEORY OF EVIDENCE

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Journal of Electronics(China) 2012年第Z1期 142-147页

作者： deng xinyang* Xu Peida** deng Yong* ** *(School of Computer and Information Science, Southwest University, Chongqing 400715, China) **(School of Electronics and Information Technology, Shanghai Jiaotong University, Shanghai 200240, China)

Transmembrane proteins are some special and important proteins in cells. Because of their importance and specificity, the prediction of the transmembrane regions has very important theoretical and practical significance. At present, the prediction methods are mainly based on the physicochemical property and statistic analysis of amino acids. However, these methods are suitable for some environments but inapplicable for other environments. In this paper, the multi-sources information fusion theory has been introduced to predict the transmembrane regions. The proposed method is test on a data set of transmembrane proteins. The results show that the proposed method has the ability of predicting the transmembrane regions as a good performance and powerful tool.

关键词： Transmembrane regions Prediction Dempster-Shafer theory of evidence Proteins