Pignistic Belief Transform: A New Method of Conflict Measurement

Cai, Qixuan; Gao, Xiaozhuan; Deng, Yong

doi:10.1109/access.2020.2966821

Cited by 18 publications

(9 citation statements)

References 76 publications

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“…In D-S evidence theory, pignistic probability transform is described as allocating the belief to each proposition equally [37]. The essence is the influence of the intersection between propositions on proposition's belief degree.…”

Section: Ppt Entropymentioning

confidence: 99%

Conflict Management for Target Recognition Based on PPT Entropy and Entropy Distance

Hou

Deng

et al. 2021

Energies

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Conflicting evidence affects the final target recognition results. Thus, managing conflicting evidence efficiently can help to improve the belief degree of the true target. In current research, the existing approaches based on belief entropy use belief entropy itself to measure evidence conflict. However, it is not convincing to characterize the evidence conflict only through belief entropy itself. To solve this problem, we comprehensively consider the influences of the belief entropy itself and mutual belief entropy on conflict measurement, and propose a novel approach based on an improved belief entropy and entropy distance. The improved belief entropy based on pignistic probability transformation function is named pignistic probability transformation (PPT) entropy that measures the conflict between evidences from the perspective of self-belief entropy. Compared with the state-of-the-art belief entropy, it can measure the uncertainty of evidence more accurately, and make full use of the intersection information of evidence to estimate the degree of evidence conflict more reasonably. Entropy distance is a new distance measurement method and is used to measure the conflict between evidences from the perspective of mutual belief entropy. Two measures are mutually complementary in a sense. The results of numerical examples and target recognition applications demonstrate that our proposed approach has a faster convergence speed, and a higher belief degree of the true target compared with the existing methods.

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Section: Ppt Entropymentioning

confidence: 99%

Conflict Management for Target Recognition Based on PPT Entropy and Entropy Distance

Hou

Deng

et al. 2021

Energies

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“…Dempster-Shafer Evidence Theory as a standard mathematical tool to model multiple-source information fusion problem Dempster (2008); Shafer (2016) has been widely researched many years. In recent years, many researchers continuously enrich the content of D-S theory, such as fusion rules Song et al (2015b); Denoeux (2008); Dutta (2018), conflict management methods Cai et al (2020); Liu et al (2019a); Murphy (2000), and entropy Yan and Deng (2020); . Moreover, the proposed method is also based on the theoretical framework, so the D-S theory is briefly introduced as follows.…”

Section: Dempster-shafer Evidence Theorymentioning

confidence: 99%

Visualization of basic probability assignment

Long¹,

Peng²,

Deng³

2021

Preprint

Self Cite

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Applying geometry to the analysis and interpretation of basic probability assignment(BPA) is a unique research direction in evidence theory. Though the geometric representation of BPA has been proposed, the visualization method of BPA is still lack of sufficient research. In this paper, we propose a new BPA visualization method based on the vector representation of the BPA to illustrate the image of BPA directly. The basic point and the uncertain vectors can be obtained by the given BPA firstly, and then we connect these components to construct the image of BPA. Through the image of BPA, we can effectively analyze the interaction effect of focal elements in BPA, and observe the potential characteristics of BPA directly. Meanwhile, the geometric meanings of parameters in the vector representation of the BPA can be explained. Finally, the advantages and applications have been studied and discussed.

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“…The most important concept of D-S theory is BPA [54][55][56], which has many extended operations, like negation [57], correlation [58][59][60], Pignistic belief transform [61], belief entropy [62][63][64], and information quality [65]. Deng proposed the concept of generalized basic probability assignment (GBPA) based on BPA.…”

Section: Generalized Basic Probability Assignmentmentioning

confidence: 99%

An improved approach to generate generalized basic probability assignment based on fuzzy sets in the open world and its application in multi-source information fusion

Fan

Xiao

2020

Appl Intell

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The generalized evidence theory (GET) is an efficient mathematical methodology to deal with multi-source information fusion problems. The GET has the capability of handling uncertain problems even in the open world. In real world applications, some noise or other disturbance often makes the multi-source information have uncertainty. Thus, how to reliably generate the generalized basic probability assignment (GBPA) is a key problem of GET, especially under the noisy environment. Therefore, in this paper, we propose a novel approach to generate GBPA with high robustness by using a cluster method. In this way, the proposed model has the ability to correctly identify the target even under a noisy environment. In particular, the k-means++ algorithm based on triangular fuzzy number is applied to build the GBPA generation model. According to the proposed GBPA generation model, the related similarity degree is calculated for each test instance. After resolving the existing conflicts, the final GBPAs are obtained by using the generalized combination rule. To demonstrate the effectiveness of the proposed method, we compare the proposed approach with related work in the applications of classification and fault diagnosis problems, respectively. Through experimental analysis, it is verified that the proposed approach has the best robustness to generate the GBPAs and maintain a high recognition rate under both noisy and noiseless environments.

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Pignistic Belief Transform: A New Method of Conflict Measurement

Cited by 18 publications

References 76 publications

Conflict Management for Target Recognition Based on PPT Entropy and Entropy Distance

Conflict Management for Target Recognition Based on PPT Entropy and Entropy Distance

Visualization of basic probability assignment

An improved approach to generate generalized basic probability assignment based on fuzzy sets in the open world and its application in multi-source information fusion

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