Title :
The evolutionary-programming learning of linguistic fuzzy model for nonlinear system and designing of configuration for neural network
Author :
Xiaolan, Wang ; Huizhong, Wang ; Debao, Chen
Author_Institution :
Coll. of Electr. & Inf. Eng., GanSu Univ. of Technol., Lanzhou, China
Abstract :
With the difficulty in building model of nonlinear system, the improving evolutionary programming in this paper is used to obtain a linguistic fuzzy model of the system by input-output data. A hierarchical evolutionary programming for RBF neural networks design is also proposed to train network configuration and parameters, overcoming shortcoming of grade algorithm The effectiveness of the evolutionary programming and the hierarchical evolutionary programming is proved through simulating SISO and MISO system.
Keywords :
evolutionary computation; fuzzy neural nets; learning (artificial intelligence); modelling; nonlinear systems; radial basis function networks; I/O data; RBF neural networks; evolutionary-programming learning; hierarchical evolutionary programming; input-output data; linguistic fuzzy model; network configuration training; network parameter training; neural network configuration design; nonlinear system modelling; Algorithm design and analysis; Data engineering; Design engineering; Educational institutions; Fuzzy neural networks; Fuzzy systems; Genetic programming; Neural networks; Nonlinear systems; Physics;
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
DOI :
10.1109/WCICA.2002.1020107
