ER-IVMF: Evidential Reasoning Based on Information Volume of Mass Function-Reference-Cited by-同舟云学术

ER-IVMF: Evidential Reasoning Based on Information Volume of Mass Function

Published:2024-01-20 Issue:1 Volume:28 Page:186-195
ISSN:1883-8014
Container-title:Journal of Advanced Computational Intelligence and Intelligent Informatics
language:en
Short-container-title:JACIII

Author:

Mao Kun¹^ORCID,Wang Yanni²^ORCID,Ma Weiwei³,Ye Jiangang⁴,Zhou Wen⁴

Affiliation:

1. Faculty of Information Engineering, Quzhou College of Technology, No.18 Jiangyuan Road, Kecheng District, Quzhou 324000, China

2. Institute of Artificial Intelligence in Sports, Capital University of Physical Education and Sports, No.11 West Road, North Third Ring Road, Haidian District, Beijing 100191, China

3. Faculty of Business Administration, Shanxi University of Finance and Economics, No.140 Wucheng Road, Taiyuan 030006, China

4. R&D Center, Quzhou Special Equipment Inspection Center, No.592 Leyuan Road, Kecheng District, Quzhou 324000, China

Abstract

Evidential reasoning (ER) under uncertainty is essential for various applications such as classification, prediction, and clustering. The effective realization of ER is still an open issue. Reliability plays a decisive role in the final performance as a major parameter of ER, reflecting the evidence’s inner information. This paper proposed ER based on the information volume of the mass function (ER-IVMF), which considers both weight and reliability. Numerical examples were designed to illustrate the effectiveness of the ER-IVMF. Additionally, a sports scoring system experiment was conducted to validate the superiority of the ER-IVMF. Considering the reliability based on high-order evidence information, the output of the proposed method was more accurate than that of the other methods. The experimental results proved that the proposed method was practical for addressing sports-scoring problems.

Funder

Beijing Social Science Foundation

Quzhou Science and Technology Project of China

Department of Education of Zhejiang Province

Zhejiang Provincial Administration

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

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