DocumentCode :
678400
Title :
The Optimization of Fuzzy Neural Network Based on Artificial Fish Swarm Algorithm
Author :
Lei Yanmin ; Feng Zhibin
Author_Institution :
Dept. of Electron. Inf. Eng., Changchun Univ., Changchun, China
fYear :
2013
fDate :
11-13 Dec. 2013
Firstpage :
469
Lastpage :
473
Abstract :
To better solve the optimization problem of fuzzy neural network (FNN), a kind of method based on artificial fish swarm algorithm (AFSA) is proposed in this paper. Aiming at the structure optimization problem of FNN, AFSA-FNN1 is established and realizes the simplification of fuzzy rules. Aiming at the parameter optimization problem of FNN, AFSA-FNN2 is built and realizes the acquisition of parameters of membership function (MF) automatically. The proposed method uses for path planning of the robot, simulation results show that the optimized FNN can enhance the smoothness of the path.
Keywords :
fuzzy control; fuzzy neural nets; mobile robots; neurocontrollers; optimisation; path planning; AFSA-FNN1; AFSA-FNN2; MF; artificial fish swarm algorithm; fuzzy neural network optimization; fuzzy rules; membership function; optimized FNN; parameter optimization problem; path planning; robot; structure optimization problem; Fuzzy control; Fuzzy neural networks; Marine animals; Optimization; Path planning; Robots; Training; artificial fish swarm algorithm; fuzzy neural network; path planning;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Mobile Ad-hoc and Sensor Networks (MSN), 2013 IEEE Ninth International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-0-7695-5159-3
Type :
conf
DOI :
10.1109/MSN.2013.93
Filename :
6726377
Link To Document :
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