New Ideas in Fuzzy Clustering and Fuzzy Automata
| Autor: | Elmawati L. Sutanto, Kevin Warwick |
|---|---|
| Rok vydání: | 1998 |
| Předmět: |
Fuzzy clustering
Fuzzy classification Neuro-fuzzy Mathematics::General Mathematics Computer science Fuzzy Control Language business.industry Type-2 fuzzy sets and systems Defuzzification Theoretical Computer Science ComputingMethodologies_PATTERNRECOGNITION Computational Theory and Mathematics Artificial Intelligence Fuzzy set operations Fuzzy number Artificial intelligence business computer Software computer.programming_language |
| Zdroj: | Scopus-Elsevier |
| ISSN: | 2326-005X 1079-8587 |
| DOI: | 10.1080/10798587.1998.10750718 |
| Popis: | In this paper a close look is taken at the concepts of fuzzy clustering and fuzzy automata. In both instances fuzzy concepts are being applied to provide a medium level of intelligent behaviour in order to operate on and provide directives for low level control. The mean-tracking clustering algorithm which has been shown to be both computationally efficient and practically extremely useful, is explained and a fuzzy version of this is introduced. A direct link between fuzzy clustering and Radial Basis Function Neural Networks is then discussed and it is shown how, under certain circumstances, the two are in fact the same. Finally a new look is taken at fuzzy automata and their practical realisation. |
| Databáze: | OpenAIRE |
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