Title :
Generating fuzzy rule-based systems from examples
Author :
Chang, Te-Min ; Yih, Yuehwern
Author_Institution :
Sch. of Ind. Eng., Purdue Univ., West Lafayette, IN, USA
Abstract :
This paper proposes a general methodology to generate fuzzy rule-based systems automatically from examples. The objective of this work is to generate fuzzy systems with good mapping ability and generalization ability as well. This methodology consists of five steps. Inductive learning is incorporated to enhance fuzzy system´s generalization ability. Experiments are conducted to evaluate the system performance of generated fuzzy systems based on two sets of data in the literature
Keywords :
fuzzy systems; generalisation (artificial intelligence); knowledge based systems; learning by example; fuzzy rule-based systems; generalization; inductive learning; mapping ability; Control engineering; Data mining; Function approximation; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Industrial engineering; Knowledge based systems; System performance; Training data;
Conference_Titel :
Fuzzy Systems Symposium, 1996. Soft Computing in Intelligent Systems and Information Processing., Proceedings of the 1996 Asian
Conference_Location :
Kenting
Print_ISBN :
0-7803-3687-9
DOI :
10.1109/AFSS.1996.583550
