Level identification using input data mining for hierarchical fuzzy system
Wong, K.W. and Gedeon, T. (2001) Level identification using input data mining for hierarchical fuzzy system. In: The Seventh Australian and New Zealand Intelligent Information Systems Conference, 18-21 Nov. 2001, Perth, W.A pp. 379-383.
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Fuzzy rule based systems have been very popular in many control applications. However, when fuzzy control systems are used in real problems, many rules may be required. A hierarchical fuzzy system that partitions a problem for more efficient computation may be the answer. When creating a hierarchical fuzzy system, the level identification stage is crucial and time-consuming. This has a direct effect on how efficient the hierarchical fuzzy system is. This paper reports the use of an input data mining technique to efficiently perform the level identification stage. Without the use of input data mining, k*(k-1) ways of building the hierarchical fuzzy system must be tried.
|Publication Type:||Conference Paper|
|Murdoch Affiliation:||School of Information Technology|
|Copyright:||© 2001 IEEE|
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