Title :
Fuzzy mean point clustering neural network
Author :
Patil, P.M. ; Kulkarni, U.V. ; Sontakke, T.R.
Abstract :
Fuzzy mean point clustering neural network (FMPCNN) is proposed with its learning algorithm, which utilizes fuzzy sets as pattern clusters. The performance of FMPCNN when verified with Fisher Iris data, it is found superior to Simpson´s fuzzy min-max neural network and fuzzy hyperline segment clustering neural network (FHLSCNN) proposed by Kulkarni and Sontakke.
Keywords :
fuzzy neural nets; fuzzy set theory; learning (artificial intelligence); pattern clustering; FMPCNN; Fisher Iris data; fuzzy hyperline segment clustering neural network; fuzzy mean point clustering neural network; fuzzy min-max neural network; fuzzy sets; learning algorithm; pattern clusters; Clustering algorithms; Computer science; Educational institutions; Fuzzy neural networks; Fuzzy sets; Iris; Network topology; Neural networks; Pattern clustering; Pattern recognition;
Conference_Titel :
Neural Information Processing, 2002. ICONIP '02. Proceedings of the 9th International Conference on
Print_ISBN :
981-04-7524-1
DOI :
10.1109/ICONIP.2002.1198184
