Publication: An ELM based multi-agent system and its applications to power generation
Date
2018
Authors
Yaw C.T.
Wong S.Y.
Yap K.S.
Yap H.J.
Amirulddin U.A.U.
Tan S.C.
Journal Title
Journal ISSN
Volume Title
Publisher
IOS Press
Abstract
This paper presents an implementation of Extreme Learning Machine (ELM) in the Multi-Agent System (MAS). The proposed method is a trust measurement approach namely Certified Belief in Strength (CBS) for Extreme Learning Machine in Multi-Agent Systems (ELM-MAS-CBS). The CBS is applied on the individual agents of MAS, i.e., ELM neural network. The trust measurement is introduced to compute reputation and strength of the individual agents. Strong elements that are related to the ELM agents are assembled to form the trust management in which will be letting the CBS method to improve the performance in MAS. The efficacy of the ELM-MAS-CBS model is verified with several activation functions using benchmark datasets (i.e., Pima Indians Diabetes, Iris and Wine) and real world applications (i.e., circulating water systems and governor). The results show that the proposed ELM-MAS-CBS model is able to achieve better accuracy as compared with other approaches. � 2018 - IOS Press and the authors. All rights reserved.
Description
Benchmarking; Electric circuit breakers; Knowledge acquisition; Learning systems; Neural networks; Pattern recognition; Power generation; Activation functions; Benchmark datasets; Certified belief in strength; Circulating water system; Extreme learning machine; ITS applications; Trust management; Trust measurement; Multi agent systems