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An ELM based multi agent systems using certified belief in strength

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dc.citedby2
dc.contributor.authorYaw C.T.en_US
dc.contributor.authorYap K.S.en_US
dc.contributor.authorYap H.J.en_US
dc.contributor.authorAmirulddin U.A.U.en_US
dc.contributor.authorid36560884300en_US
dc.contributor.authorid24448864400en_US
dc.contributor.authorid35319362200en_US
dc.contributor.authorid26422804600en_US
dc.date.accessioned2023-05-16T02:46:44Z
dc.date.available2023-05-16T02:46:44Z
dc.date.issued2014
dc.description.abstractA trust measurement method called certified belief in strength (CBS) for Extreme Learning Machine (ELM) Multi Agent Systems (MAS) is proposed in this paper. The CBS method is used to improve the performance of the individual agents of the MAS, i.e., ELM neural network. Then, trust measurement is achieved based on reputation and strength of the individual agents. In addition, trust is assemble from strong elements that are associated with the CBS which let the ELM to improve the performance of the MAS. The efficiency of the ELM-MAS-CBS model is verified with several activation function using benchmark datasets which are Pima Indians Diabetes (PID), Iris and Wine. The results show that the proposed ELM-MAS-CBS model is able to achieve better accuracy as compared with other approaches. © Springer International Publishing Switzerland 2014.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/978-3-319-12643-2_56
dc.identifier.epage465
dc.identifier.scopus2-s2.0-84910022084
dc.identifier.spage458
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84910022084&doi=10.1007%2f978-3-319-12643-2_56&partnerID=40&md5=61c0e3fc39b65260c79b4897f41e493f
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22024
dc.identifier.volume8836
dc.publisherSpringer Verlagen_US
dc.sourceScopus
dc.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.titleAn ELM based multi agent systems using certified belief in strengthen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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