A fuzzy ensemble of parallel polynomial neural networks with information granules formed by fuzzy clustering

Knowledge-Based Systems

Volumn 23, Issue 3, 2010, Pages 202-219

  Roh, Seok Beom ^a   Oh, Sung Kwun ^b   Pedrycz, Witold ^c,d  

^a Wonkwang University   (South Korea)

^b Suwon University   (South Korea)

^c UNIVERSITY OF ALBERTA   (Canada)

^d SYSTEMS RESEARCH INSTITUTE   (Poland)

Author keywords

Fuzzy C means; Fuzzy ensemble; Information granules; Polynomial neural networks

Indexed keywords

ACTIVATION LEVEL; APPROXIMATION ABILITY; DESIGN PROCEDURE; FUZZY C MEAN; FUZZY C MEANS CLUSTERING; FUZZY MODELS; GENERALIZATION CAPABILITY; HIGH DIMENSIONALITY; HIGHLY NONLINEAR; INFORMATION GRANULES; INPUT SPACE; INPUT VARIABLES; LOCAL LEARNING; LOCAL MODEL; LOCAL REGION; NEURO-FUZZY MODELING; OPTIMAL VALUES; OUTPUT VARIABLES; PARALLEL POLYNOMIALS; POLYNOMIAL NEURAL NETWORKS; WEIGHTED LEAST SQUARE ESTIMATION;

FUZZY CLUSTERING; FUZZY RULES; FUZZY SYSTEMS; GRANULATION; INFORMATION USE; LEARNING ALGORITHMS; MACHINE DESIGN; POLYNOMIAL APPROXIMATION;

FUZZY NEURAL NETWORKS;

EID: 77549083109     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2009.12.002     Document Type: Article

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