The Improved Combination Rule of D Numbers and Its Application in Radiation Source Identification

Guan, Xinping; Liu, Haiqiao; Xiao, Yi; Zhao, Jing

doi:10.1155/2018/6025680

Cited by 15 publications

(12 citation statements)

References 40 publications

(52 reference statements)

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“…On one hand, researchers have done a lot of researches to improve the theory framework. Since the combination rule of D numbers does not satisfy the commutativity and combinability, Xin et al proposed to simplify the combination rule [41]. Deng et al proposed a method to measure the uncertainty of D number based on belief interval [42] while Xia et al used the entropy function to define the uncertainty of the D number [43].…”

Section: Introductionmentioning

confidence: 99%

Risk Assessment on Offshore Photovoltaic Power Generation Projects in China Using D Numbers and ANP

Jie

Qian

2020

IEEE Access

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At present, China's offshore photovoltaic (PV) industry is developing rapidly. Risk assessment on offshore PV power generation (OPVPG) projects is important. The existing risk assessment methods in OPVPG projects in China are insufficient in dealing with different types of uncertainties. In this paper, we propose a computational model based on D Numbers and analytic network process (ANP) method to handle risk assessment on OPVPG projects. Firstly, factors that influencing offshore photovoltaic power generation projects in China are identified and the weights of the factors are determined by domain analyst using ANP. Secondly, risk evaluation judgment on each factor is given by expert referring to predefined anchors and linguistic labels under specific situations. Thirdly, the judgments are represented as D numbers and are integrated into a fused D number. Finally, the overall risk level of OPVPG in China is obtained based on the fused D number. The main contribution of the proposed method based on D numbers is to deal with uncertainties and the degree of confidence in experts judgments. Uncertainty includes situations like: do not know how to assign accurate beliefs to risk levels and incomplete frame of discernment. The degree of confidence shows the cognition of the experts. The situation that the confidence of expert is equal to 1 shows the certainty of experts. When the confidence of expert is equal to 0, it means that experts cannot decide the risk levels. It can be considered as a new strategy for risk assessment and enriches the framework of decision-making. Several case studies are illustrated to show the effectiveness and flexibility of the proposed method.

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Section: Introductionmentioning

confidence: 99%

Risk Assessment on Offshore Photovoltaic Power Generation Projects in China Using D Numbers and ANP

Jie

Qian

2020

IEEE Access

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“…New combination rule can effectively solve problems in recognition field. In [ 28 ], the improved combination rule of D-number is applied to emitter identification. In [ 29 ], a method is proposed to select the source behavior, which is based on a very general and expressive fusion scheme.…”

Section: Introductionmentioning

confidence: 99%

Improved Base Belief Function-Based Conflict Data Fusion Approach Considering Belief Entropy in the Evidence Theory

Lei

Tang

2020

Entropy

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Due to the nature of the Dempster combination rule, it may produce results contrary to intuition. Therefore, an improved method for conflict evidence fusion is proposed. In this paper, the belief entropy in D–S theory is used to measure the uncertainty in each evidence. First, the initial belief degree is constructed by using an improved base belief function. Then, the information volume of each evidence group is obtained through calculating the belief entropy which can modify the belief degree to get the final evidence that is more reasonable. Using the Dempster combination rule can get the final result after evidence modification, which is helpful to solve the conflict data fusion problems. The rationality and validity of the proposed method are verified by numerical examples and applications of the proposed method in a classification data set.

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“…Aiming to overcome the above mentioned deficiencies of evidence theory, D number theory has emerged in 2012, which provides a more flexible way to deal with uncertain information, and the above mentioned limitations are well addressed. Since the advantage of D number theory, it has been widely carried out to solve these problems, such as decision making [65][66][67], location selection [68], risk assessment [69], supply chain management [70], target recognition [71], environmental impact assessment [72,73], curtain grouting efficiency assessment [74] and so forth [75][76][77]. Besides, D number thoery can be together used with other measures, such as intuitionistic hesitant fuzzy set [78], decision-making trial and evaluation laboratory method (DEMATEL) [79], failure mode and effect analysis (FMEA) [80], to generate new measures for some real-life problems.…”

Section: Introductionmentioning

confidence: 99%

A New Evaluation Methodology for Quality Goals Extended by D Number Theory and FAHP

2020

Information

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Evaluation of quality goals is an important issue in process management, which essentially is a multi-attribute decision-making (MADM) problem. The process of assessment inevitably involves uncertain information. The two crucial points in an MADM problem are to obtain weight of attributes and to handle uncertain information. D number theory is a new mathematical tool to deal with uncertain information, which is an extension of evidence theory. The fuzzy analytic hierarchy process (FAHP) provides a hierarchical way to model MADM problems, and the comparison analysis among attributes is applied to obtain the weight of attributes. FAHP uses a triangle fuzzy number rather than a crisp number to represent the evaluation information, which fully considers the hesitation to give a evaluation. Inspired by the features of D number theory and FAHP, a D-FAHP method is proposed to evaluate quality goals in this paper. Within the proposed method, FAHP is used to obtain the weight of each attribute, and the integration property of D number theory is carried out to fuse information. A numerical example is presented to demonstrate the effectiveness of the proposed method. Some necessary discussions are provided to illustrate the advantages of the proposed method.

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The Improved Combination Rule of D Numbers and Its Application in Radiation Source Identification

Cited by 15 publications

References 40 publications

Risk Assessment on Offshore Photovoltaic Power Generation Projects in China Using D Numbers and ANP

Risk Assessment on Offshore Photovoltaic Power Generation Projects in China Using D Numbers and ANP

Improved Base Belief Function-Based Conflict Data Fusion Approach Considering Belief Entropy in the Evidence Theory

A New Evaluation Methodology for Quality Goals Extended by D Number Theory and FAHP

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