Design of K-means clustering-based polynomial radial basis function neural networks (pRBF NNs) realized with the aid of particle swarm optimization and differential evolution

Neurocomputing

Volumn 78, Issue 1, 2012, Pages 121-132

  Oh, Sung Kwun ^a   Kim, Wook Dong ^a   Pedrycz, Witold ^b,c   Joo, Su Chong ^d  

^a Suwon University   (South Korea)

^b UNIVERSITY OF ALBERTA   (Canada)

^c SYSTEMS RESEARCH INSTITUTE   (Poland)

^d Wonkwang University   (South Korea)

Author keywords

Differential evolution algorithm; K means clustering; Particle swarm optimization; Polynomial radial basis function neural networks (p RBF NNs); Weighted least square estimation (WLSE).

Indexed keywords

ADVANCED ARCHITECTURE; COMPARATIVE ANALYSIS; COMPREHENSIVE DESIGNS; DATA SETS; DIFFERENTIAL EVOLUTION; DIFFERENTIAL EVOLUTION ALGORITHMS; FUNCTIONAL CONNECTION; K-MEANS; K-MEANS CLUSTERING; K-MEANS CLUSTERING ALGORITHM; NONLINEAR FUNCTIONS; PARTICLE SWARM; RADIAL BASIS FUNCTION NEURAL NETWORKS; RECEPTIVE FIELDS; TWO MACHINES; WEIGHTED LEAST SQUARE ESTIMATION;

CLUSTERING ALGORITHMS; DESIGN; ESTIMATION; NETWORK ARCHITECTURE; NEURAL NETWORKS; PARTICLE SWARM OPTIMIZATION (PSO); POLYNOMIALS;

RADIAL BASIS FUNCTION NETWORKS;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; CLUSTER ANALYSIS; CONTROLLED STUDY; EVOLUTIONARY ALGORITHM; FUZZY SYSTEM; GENETIC ALGORITHM; LINGUISTICS; MACHINE LEARNING; METHODOLOGY; NONLINEAR SYSTEM; PRIORITY JOURNAL; PROCESS DESIGN; PROCESS OPTIMIZATION; RADIAL BASED FUNCTION; RECEPTIVE FIELD; REGRESSION ANALYSIS; VELOCITY;

EID: 82655162109     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2011.06.031     Document Type: Article

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