Constructing hierarchical fuzzy rule bases for classification
T.D. Gedeon, Kok Wai Wong, Domonkos Tikk · 2002
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. The number of rules required depends on the number of inputs and the number of fuzzy linguistic terms used. This exponential explosion of fuzzy rules can take too much computing time to solve any but the simplest problems. This paper proposes a hierarchical fuzzy system that partitions a problem for more efficient computation. The hierarchical fuzzy rule base algorithm constructs rules from data for the purpose of performing fuzzy classification. Illustration examples are also generated and the results show that this hierarchical fuzzy system can be successfully used for classification applications.