| Application of evidence theory in information fusion of multiple sources in bayesian analysis |
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| 作者姓名： | 周忠宝 蒋平 武小悦 |
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| 作者单位： | CollegeofHumanitiesandManagement,NationalUniversityofDefenseTechnology,Changsha,410073,China |
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| 摘 要： | How to obtain proper prior distribution is one of the most critical problems in Bayesian analysis. In many practical cases, the prior information often comes from different sources, and the prior distribution form could be easily known in some certain way while the parameters are hard to determine. In this paper, based on the evidence theory, a new, method is presented to fuse the information of multiple sources and determine the parameters of the prior distribution when tile form is known. By taking the prior distributions which result from the infornlation of multiple sources and converting them into corresponding mass functions which can be combined by Dempster-Shafer (D-S) method, we get the combined mass function and the representative points of the prior distribution. These points are used to fit with the given distribution form to determine the parameters of the prior distribution. And then the fused prior distribution is obtained and Bayesian analysis can be performed. How to convert the prior distributions into mass functions properly and get the representative points of the fused prior distribution is the central question we address m this paper. The simulation example shows that the proposed method is effective.
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| 关 键 词： | 信息融合 贝叶斯分析 证据理论 优先权分布 D-S方法 |
Application of evidence theory in information fusion of multiple sources in bayesian analysis |
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| ZHOU Zhong-bao,JIANG Ping,WU Xiao-yue.Application of evidence theory in information fusion of multiple sources in bayesian analysis[J].Journal of Harbin Institute of Technology,2004,11(4):461-463. |
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| Authors: | ZHOU Zhong-bao JIANG Ping WU Xiao-yue |
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| Abstract: | How to obtain proper prior distribution is one of the most critical problems in Bayesian analysis. In many practical cases, the prior information often comes from different sources, and the prior distribution form could be easily known in some certain way while the parameters are hard to determine. In this paper, based on the evidence theory, a new method is presented to fuse the information of multiple sources and determine the parameters of the prior distribution when the form is known. By taking the prior distributions which result from the information of multiple sources and converting them into corresponding mass functions which can be combined by Dempster-Shafer (D-S) method, we get the combined mass function and the representative points of the prior distribution. These points are used to fit with the given distribution form to determine the parameters of the prior distribution. And then the fused prior distribution is obtained and Bayesian analysis can be performed. How to convert the prior distributions into mass functions properly and get the representative points of the fused prior distribution is the central question we address in this paper. The simulation example shows that the proposed method is effective. |
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| Keywords: | Bayesian analysis evidence theory D-S method information fusion |
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