Fuzzy clustering improves convergence of the backpropagation algorithm

Proceedings of the ACM Symposium on Applied Computing

Volumn 02-February-1998, Issue , 1998, Pages 277-281

  Abunawass, Adel M ^a   Bhella, Opinderjit Singh ^a   Ding, Min ^a   Li, Weiqun ^a  

^a WESTERN ILLINOIS UNIVERSITY   (United States)

Author keywords

Artificial intelligence; Backpropagation; Fuzzy clustering; Fuzzy logic; Neural networks

Indexed keywords

ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; CLUSTERING ALGORITHMS; COMPUTATION THEORY; COMPUTER CIRCUITS; ERRORS; FUZZY CLUSTERING; FUZZY NEURAL NETWORKS; NEURAL NETWORKS;

ALGORITHM'S PERFORMANCE; CLUSTERING TECHNIQUES; CONVERGENCE SPEED; DEGREE OF SIMILARITY; ERROR SIGNAL; FUZZY CONCEPT; NEURAL NETWORK MODEL; RATE OF CONVERGENCE;

FUZZY LOGIC;

EID: 85002002655     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/330560.330704     Document Type: Conference Paper

References (10)

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