Parameter estimation based on interval-valued belief structures |
| |
| Authors: | Xinyang Deng Yong Hu Felix T.S. Chan Sankaran Mahadevan Yong Deng |
| |
| Affiliation: | 1. School of Computer and Information Science, Southwest University, Chongqing, 400715, China;2. Institute of Business Intelligence and Knowledge Discovery, Guangdong University of Foreign Studies, Sun Yat-Sen University, Guangzhou, 510006, China;3. Department of Industrial and Systems Engineering, Hong Kong Polytechnic University, Hong Kong, China;4. School of Automation, Northwestern Polytechnical University, Xian, 710072, China;5. School of Engineering, Vanderbilt University, Nashville, TN, 37235, USA |
| |
| Abstract: | Parameter estimation based on uncertain data represented as belief structures is one of the latest problems in the Dempster–Shafer theory. In this paper, a novel method is proposed for the parameter estimation in the case where belief structures are uncertain and represented as interval-valued belief structures. Within our proposed method, the maximization of likelihood criterion and minimization of estimated parameter’s uncertainty are taken into consideration simultaneously. As an illustration, the proposed method is employed to estimate parameters for deterministic and uncertain belief structures, which demonstrates its effectiveness and versatility. |
| |
| Keywords: | Parameter estimation Interval-valued belief structures Dempster&ndash Shafer theory Belief function Maximum likelihood estimation |
| 本文献已被 ScienceDirect 等数据库收录！ |
|
