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author:

Yang, Long-Hao (Yang, Long-Hao.) [1] (Scholars:杨隆浩) | Liu, Jun (Liu, Jun.) [2] | Wang, Ying-Ming (Wang, Ying-Ming.) [3] (Scholars:王应明) | Martinez, Luis (Martinez, Luis.) [4]

Indexed by:

CPCI-S

Abstract:

One of eminent activity recognition approaches is based on the extended belief rule-based system (EBRBS), which shows an excellent robustness comparing with many traditional approaches. For this reason, three versions of EBRBSs, namely original EBRBS (O-EBRBS), DRA-EBRBS, and Micro-EBRBS, are adapted in the comparative analysis to illustrate the performance of these EBRBSs. Results demonstrate that the Micro-EBRBS can produce a satisfied accuracy under less time of inference scheme and fewer numbers of activated rules comparing to the O-EBRBS and DRA-EBRBS.

Keyword:

activity recognition comparative analysis Extended belief rule-based system

Community:

  • [ 1 ] [Yang, Long-Hao]Fuzhou Univ, Decis Sci Inst, Fuzhou 350116, Fujian, Peoples R China
  • [ 2 ] [Wang, Ying-Ming]Fuzhou Univ, Decis Sci Inst, Fuzhou 350116, Fujian, Peoples R China
  • [ 3 ] [Yang, Long-Hao]Univ Jaen, Dept Comp Sci, Jaen, Spain
  • [ 4 ] [Martinez, Luis]Univ Jaen, Dept Comp Sci, Jaen, Spain
  • [ 5 ] [Liu, Jun]Ulster Univ, Sch Comp & Math, Coleraine, Londonderry, North Ireland
  • [ 6 ] [Wang, Ying-Ming]Fuzhou Univ, Minist Educ, Key Lab Spatial Data Min & Informat Sharing, Fuzhou 350116, Fujian, Peoples R China

Reprint 's Address:

  • 王应明

    [Wang, Ying-Ming]Fuzhou Univ, Decis Sci Inst, Fuzhou 350116, Fujian, Peoples R China

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Source :

DATA SCIENCE AND KNOWLEDGE ENGINEERING FOR SENSING DECISION SUPPORT

Year: 2018

Volume: 11

Page: 430-436

Language: English

Cited Count:

WoS CC Cited Count: 3

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 2

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