An Improved Belief Entropy in Evidence Theory

Yan, Hangyu; Deng, Yong

doi:10.1109/access.2020.2982579

Cited by 40 publications

(39 citation statements)

References 93 publications

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“…The traditional methods (such as AHP [30] and DEMATEL [29]) have decision compensation in the evaluation, that is, the high value of one attribute can make up for the low value of other attributes. The core idea of PROMETHEE II is outranking method [47][48][49][50]. The preference function is used to compare two objects one by one, and the preference order of all objects is finally determined, thus avoiding the influence of compensation on the decision results.…”

Section: Integration Of Complex Network Modeling and Promethee IImentioning

confidence: 99%

“…According to evidence theory [46][47][48], m alternatives of intelligent manufacturing project in the sustainability assessment problem are treated as the elements in the discernment frame. Therefore, the discernment frame is defined as follows.…”

Section: Two-stage Evidence Combinationmentioning

confidence: 99%

“…The most basic information carrier in evidence theory is called basic probability assignment (BPA) [46][47][48] (27) where "  "is the symbol of combination of multiple mass functions and (…”

Section: Two-stage Evidence Combinationmentioning

confidence: 99%

“…(3) Object evaluation. Dempster Shafer theory (D-S theory) [46][47][48] can directly express uncertainty, which provides an effective method for the expression and synthesis of uncertain information. This paper creatively applies D-S theory to assessment problem.…”

Section: Introductionmentioning

confidence: 99%

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Sustainability Assessment of Intelligent Manufacturing Supported by Digital Twin

et al. 2020

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As a major challenge and opportunity for traditional manufacturing, intelligent manufacturing is facing the needs of sustainable development in future. Sustainability assessment undoubtedly plays a pivotal role for future development of intelligent manufacturing. Aiming at this, the paper presents the digital twin driven information architecture of sustainability assessment oriented for dynamic evolution under the whole life cycle based on the classic digital twin mapping system. The sustainability assessment method segment of the architecture includes indicator system building, indicator value determination, indicator importance degree determination and intelligent manufacturing project assessing. A novel approach for treating the ambiguity of expert' judgment in indicator value determination by introducing trapezoidal fuzzy number into analytic hierarchy process is proposed, while the complexity of the influence relationship among the indicators is processed by the integration of complex networks modeling and PROMETHEE II for the indicator importance degree determination. A two-stage evidence combination model based on evidence theory is built for intelligent manufacturing project assessing lastly. The presented digital-twin-driven information architecture and the sustainability assessment method is tested and validated on a study of sustainability assessment of 8 intelligent manufacturing projects of an air conditioning enterprise. The results of the presented method were validated by comparing them with the results of the fuzzy and rough extension of the PROMETHEE II, TOPSIS and VIKOR methods, indicator importance degree determining method by entropy and indicator value determining method by accurate expert scoring.

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Section: Integration Of Complex Network Modeling and Promethee IImentioning

confidence: 99%

Section: Two-stage Evidence Combinationmentioning

confidence: 99%

Section: Two-stage Evidence Combinationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Sustainability Assessment of Intelligent Manufacturing Supported by Digital Twin

et al. 2020

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“…There are many mathematical expressions to measure the degree of uncertainty of information, such as Shannon entropy, 25 Rényi entropy, 26 Deng entropy, 27‐30 fuzzy entropy, 31 generalized belief entropy, 32 divergence, 33 information quality, 34 and so on. Tsallis entropy is proposed by Tsallis for the use of fractal systems 35 .…”

Section: Introductionmentioning

confidence: 99%

A method for combining conflicting evidences with improved distance function and Tsallis entropy

Xiao

2020

Int J Intell Syst

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For the sake of great ability of handling uncertain information, Dempster‐Shafer evidence theory is extensively used in information fusion. Nevertheless, when there exists highly inconsistent evidences, using classical Dempster's combination rule may lead to counter‐intuitive results. To address this issue, a new conflicting evidences combination method based on distance function and Tsallis entropy is proposed. Numerical examples are used to illustrate the feasibility and efficiency of the proposed method. Further, an fault diagnosis problem is used as an example to show the effectiveness and superiority of the proposed method. The proposed method outperforms other methods that the proposed method recognize the target by the probability 99.49%, which is higher than other methods.

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