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A data fusion method in wireless sensor network based on belief structure

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成果类型:
期刊论文
作者:
Long, Chengfeng;Liu, Xingxin;Yang, Yakun;Zhang, Tao;Tan, Siqiao;...
通讯作者:
Tang, X.;Long, C.
作者机构:
[Yang, Yakun; Tan, Siqiao; Fang, Kui; Liu, Xingxin; Long, Chengfeng; Zhang, Tao] Hunan Agr Univ, Sch Informat & Intelligence Sci & Technol, Changsha, Peoples R China.
[Tang, Xiaoyong] Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Changsha, Peoples R China.
[Yang, Gelan] Hunan City Univ, Dept Comp Sci, Yiyang, Peoples R China.
通讯机构:
[Chengfeng Long; Xiaoyong Tang] S
School of Information and Intelligence Science and Technology, Hunan Agricultural University, Changsha, China<&wdkj&>School of Computer and Communications Engineering, Changsha University of Science and Technology, Changsha, China
语种:
英文
关键词:
Wireless sensor network;Granular computing;Rough set;Dempster–Shafer theory;Reduction
期刊:
EURASIP JOURNAL ON WIRELESS COMMUNICATIONS AND NETWORKING
ISSN:
1687-1472
年:
2021
卷:
2021
期:
1
页码:
1-22
基金类别:
This research was partially funded by the National Natural Science Foundation of China (Grant No. 61972146, 61672219)
机构署名:
本校为其他机构
院系归属:
信息与电子工程学院
摘要:
Considering the issue with respect to the high data redundancy and high cost of information collection in wireless sensor nodes, this paper proposes a data fusion method based on belief structure to reduce attribution in multi-granulation rough set. By introducing belief structure, attribute reduction is carried out for multi-granulation rough sets. From the view of granular computing, this paper studies the evidential characteristics of incomplete multi-granulation ordered information systems. On this basis, the positive region reduction, belief reduction and plausibility reduction are put fo...

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