@inproceedings{bd1f63b4f4954bf9a8de8eeff927a92e,
title = "An improved evidence combination method of D-S theory",
abstract = "Dempster-Shafer evidence theory provides a useful computational scheme for integrating uncertain information from multiple sources. However, the combination result can be paradoxical when the evidences seriously conflict with each other. In this paper, we present an improved D-S algorithm which verifies the weights of conflicting evidences. Firstly, we calculate the distance between any two of the evidences by the Jousselme distance formula and obtain the entropy index of distance correspondingly by using information entropy theory. Secondly, compute the relative support degree and absolute support degree so as to modifies the basic probability assignment (BPA). Experiments show that this method has a more comprehensive consideration of conflict evidences problem and more sensitive on the differences of focal element.",
keywords = "Combination rule, Conflict, Data fusion, Dempster-Shafer theory, Information entropy",
author = "Haobin Shi and Shuyun Yang and Zhenliang Cao and Wei Pan and Weihua Li",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016 ; Conference date: 04-07-2016 Through 06-07-2016",
year = "2016",
month = aug,
day = "16",
doi = "10.1109/IS3C.2016.90",
language = "英语",
series = "Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "319--322",
booktitle = "Proceedings - 2016 IEEE International Symposium on Computer, Consumer and Control, IS3C 2016",
}