A New Synthesis Combination Rule Based on Evidential Correlation Coefficient

Zhang, Pengdan; Tian, Ye; Kang, Bingyi

doi:10.1109/access.2020.2975563

Cited by 10 publications

(3 citation statements)

References 39 publications

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“…A triangular fuzzy number effect ranking method based on fuzzy ordered weighted averaging (FOWA) [84] is formed. The method includes the following five steps to retain the advantages of paired comparison assignment and reduce information loss in the concept score matrix [85], coefficient of variation [86], and Dempster combination rule [87].…”

Section: Retrieval Of the Effect Knowledgementioning

confidence: 99%

Product Improvement Using Knowledge Mining and Effect Analogy

Wang,

Tan,

Peng

2024

Applied Sciences

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Different from new product development, design improvement aims to solve the problems of existing products. Although design knowledge and effect tools have been applied in product improvement, the existing methods for design improvement are limited in their specific application areas. A general method of product improvement is proposed in this paper using the knowledge mining and effect analogy. The length–time dimension is introduced to link the problem analysis and problem-solving for the first time. This method includes the effect knowledge base construction, length–time dimension extraction, effect retrieval, effect ranking, analogy object selection, and effect structure mapping. This method integrates a variety of algorithms and software tools in design knowledge mining to improve the efficiency of the effect analogy for product improvement. Through the comparative analysis of three effect retrieval methods and design improvement of a button battery ring device, the superiority and feasibility of the proposed method are verified.

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Section: Retrieval Of the Effect Knowledgementioning

confidence: 99%

Product Improvement Using Knowledge Mining and Effect Analogy

Wang,

Tan,

Peng

2024

Applied Sciences

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“…Several methods are raised to solve the evidence conflicts. To verify the effectiveness of the proposed DS combination method based on two revised evidences, the methods in [13,23,[28][29][30] are adopted as the comparison methods.…”

Section: Journal Of Sensorsmentioning

confidence: 99%

“…Typical modified methods of DS application are divided into two categories-the modification of synthetic equations (DS combination rule), and the revision of evidences before combination. The former methods optimize the DS combination rule by allocating conflict to certain subsets with certain proportions [27][28][29]. However, these methods sometimes violate the theoretical properties of DS combination rule like commutativity and associativity.…”

Section: Introductionmentioning

confidence: 99%

Multi-Feature Multi-Sensor Fusion for Emitter Identification Based on a Modified DS Application

et al. 2022

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Emitter identification is a crucial task in electronic countermeasure technology area, which deeply affects the accuracy of subsequent threat estimation. In emitter identification system, sensors (transmitter and receiver) have inevitable inconsistency and fuzziness, along with possible ambiguity and instability under interference and malfunction. To manage the uncertainty in emitter identification system, we propose a multi-feature multi-sensor fusion algorithm based on a modified DS application. The modified DS application for emitter identification system is accomplished by two parts—multi-feature fusion based on the improved proximity approach to obtain basic probability assignment ( B P A ) and multi-sensor fusion based on the combination of two revised evidences to solve potential evidence conflicts. Firstly, the multi-feature fusion method based on the improved proximity approach is raised to produce the identification result for each receiver, which simultaneously build B P A s for DS application. Four entropies are extracted to establish the multi-feature description of received signal. Then, in order to solve the inconsistency among different receivers and realize multi-sensor fusion for emitter identification, the multi-sensor fusion method based on the combination of two revised evidences is proposed. Two revised evidences are put forward, respectively, by the introduction of Lance distance function and spectral angle cosine function before applying DS combination. Experiments and analyses comprehensively demonstrate the great uncertainty management performance and favorable emitter identification effect of the proposed algorithm.

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