Title :
Fuzzy rules acquisition and parameters evolution based on fuzzy neural networks
Author :
Yan, Wu ; Hongbao, Shi
Author_Institution :
Inst. of Comput. Tech., Shanghai Tiedao Univ., China
Abstract :
Some methods are proposed for fuzzy rules acquisition and fuzzy system parameters tuning based on fuzzy neural networks. The feasibility of the proposed methods is tested with an experiment of automatic train operation simulation. This experiment is also used to compare the learning and control of fuzzy inference system with those of standard BP networks and basic fuzzy systems. A summary is made of the characteristics of the methods. The final result indicates that the methods of fuzzy rules generation and fuzzy system tuning are very effective
Keywords :
fuzzy neural nets; fuzzy set theory; fuzzy systems; inference mechanisms; knowledge acquisition; learning (artificial intelligence); fuzzy inference; fuzzy neural networks; fuzzy rules acquisition; fuzzy set theory; fuzzy systems; learning; parameters evolution; Analytical models; Automatic control; Computer networks; Control systems; Fuzzy control; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Input variables; Neural networks;
Conference_Titel :
Neural Networks, 1999. IJCNN '99. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5529-6
DOI :
10.1109/IJCNN.1999.830843
