Granular Neuro-fuzzy Knowledge Compression and Expansion
نویسندگان
چکیده
In order to overcome weaknesses of the conventional crisp neural network and the fuzzy-operation-oriented neural network, we have developed a general fuzzy-reasoning-oriented fuzzy neural network called a Crisp-Fuzzy Neural Network (CFNN) which is capable of extracting high-level knowledge such as fuzzy IF-THEN rules from either crisp data or fuzzy data. A CFNN can eeectively compress a 5 5 fuzzy IF-THEN rule base of a cart-pole balancing system to a 22 one, and can also expand an invalid sparse 33 fuzzy IF-THEN rule base to a valid 55 one. Therefore , a CFNN is an eecient neuro-fuzzy system with abilities of discovering new fuzzy knowledge from either numerical data or fuzzy data, compressing and expending fuzzy knowledge.
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