Novel hybrid learning algorithms for tuning ANFIS parameters using adaptive weighted PSO

IEEE International Conference on Fuzzy Systems

Volumn , Issue , 2007, Pages

  Shoorehdeli, M Aliyari ^a,b   Teshnehlab, M ^b   Sedigh, A K ^b  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b K N TOOSI UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Adaptive weighted particle swarm; ANFIS; Fuzzy systems; Identification; Neuro Fuzzy; Optimization; Recursive least square; Swarm intelligent; TSK system

Indexed keywords

ADAPTIVE ALGORITHMS; BIOELECTRIC PHENOMENA; CHLORINE COMPOUNDS; CURVE FITTING; DIESEL ENGINES; FUZZY INFERENCE; FUZZY LOGIC; FUZZY SYSTEMS; GENETIC ALGORITHMS; GEODESY; GRADIENT METHODS; LEARNING ALGORITHMS; LEARNING SYSTEMS; LEAST SQUARES APPROXIMATIONS; PARAMETER ESTIMATION;

ADAPTIVE NETWORK-BASED FUZZY INFERENCE SYSTEM; ADAPTIVE WEIGHTED PARTICLE SWARM; ANFIS; COMPLEX PLANTS; GENETIC ALGORITHM (GA); GRADIENT BASED; GRADIENT-BASED METHODS; HYBRID APPROACHES; HYBRID LEARNING ALGORITHMS; HYBRID METHODS; IDENTIFICATION; INTERNATIONAL CONFERENCES; NEURO- FUZZY; OPTIMIZATION; PARTICLE-SWARM OPTIMIZATION; RECURSIVE LEAST SQUARE; SIMULATION RESULTS; SWARM INTELLIGENT; TSK SYSTEM;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 50249107984     PISSN: 10987584     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FUZZY.2007.4295571     Document Type: Conference Paper

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