DocumentCode
1909409
Title
Evolving fuzzy clusters
Author
Fogel, David B. ; Simpson, Patrick K.
Author_Institution
Orincon Corp., San Diego, CA, USA
fYear
1993
fDate
1993
Firstpage
1829
Abstract
An alternate training technique for the fuzzy min-max clustering neural network is introduced. The original fuzzy min-max clustering neural network utilized an algorithm similar to leader clustering and adaptive resonance theory to place hyperboxes in the pattern space. An alternative clustering technique is introduced, which utilizes evolutionary programming and information criteria to produce a set of hyperboxes
Keywords
fuzzy set theory; learning (artificial intelligence); minimax techniques; neural nets; adaptive resonance theory; evolutionary programming; fuzzy min-max clustering neural network; hyperboxes; information criteria; leader clustering; learning; pattern space; Clustering algorithms; Function approximation; Fuzzy neural networks; Fuzzy sets; Genetic programming; Hypercubes; Neural networks; Resonance; Transfer functions;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993., IEEE International Conference on
Conference_Location
San Francisco, CA
Print_ISBN
0-7803-0999-5
Type
conf
DOI
10.1109/ICNN.1993.298835
Filename
298835
Link To Document