2012 ©
             Publication
Journal Publication
Research Title An improved grey wolf optimizer for training q-Gaussian Radial Basis Functional-link nets 
Date of Distribution 8 December 2014 
Conference
     Title of the Conference 2014 International Computer Science and Engineering Conference (ICSEC) 
     Organiser Department of Science, Faculty of Science, Khon Kaen University 
     Conference Place Pullman Khon Kaen Raja Orchid hotel 
     Province/State Khon Kaen, Thailand 
     Conference Date 30 July 2014 
     To 1 August 2014 
Proceeding Paper
     Volume
     Issue
     Page 209-214 
     Editors/edition/publisher  
     Abstract In this paper, a novel meta-heuristic technique an improved Grey Wolf Optimizer (IGWO) which is an improved version of Grey Wolf Optimizer (GWO) is proposed. The performance is evaluated by adopting the IGWO to training q-Gaussian Radial Basis Functional-link nets (qRBFLNs) neural networks. The function approximation problems in regression areas and the multiclass classification problem in classification areas are employed to test the algorithm. For instance, in order to overcome the multiclass classification problem, the dataset of the screening risk groups of the population age 15 years and over in Charoensin District, Sakon Nakhon Province, Thailand is used in the experiments. The results of the function approximation problems and real application in multiclass classification problem prove that the proposed algorithm is able to address the test problems. Moreover, the proposed algorithm obtains competitive performance compared to other meta-heuristic methods. 
Author
547020034-9 Mr. NIPOTEPAT MUANGKOTE [Main Author]
Science Doctoral Degree

Peer Review Status มีผู้ประเมินอิสระ 
Level of Conference นานาชาติ 
Type of Proceeding Full paper 
Type of Presentation Oral 
Part of thesis false 
Presentation awarding false 
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