Title :
Competitive learning algorithm for the fuzzy rule optimization
Author :
Dai, Fengzhi ; Li, Long ; Kushida, Naoki ; Zhang, Baolong
Author_Institution :
Coll. of Electron. Inf. & Autom., Tianjin Univ. of Sci. & Technol., Tianjin, China
Abstract :
By merging the feed forward neural network, the competitive learning algorithm and the fuzzy control, the neural network-based adaptive fuzzy control algorithm is proposed. This system can produce more reasonable fuzzy rules by the competitive (clustering) algorithm, and control the object by the optimized fuzzy rules. The analysis of the system, the experimental result and considerations are given.
Keywords :
feedforward neural nets; fuzzy set theory; optimisation; pattern clustering; clustering algorithm; competitive learning algorithm; feedforward neural network; fuzzy control; fuzzy rule optimization; neural network based adaptive fuzzy control algorithm; Algorithm design and analysis; Artificial neural networks; Clustering algorithms; Control systems; Fuzzy control; Guidelines; Training; adaptive vector quantization; competitive learning; fuzzy rule optimizing; neural network;
Conference_Titel :
Industrial Electronics and Applications (ICIEA), 2011 6th IEEE Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-8754-7
Electronic_ISBN :
pending
DOI :
10.1109/ICIEA.2011.5975691
