DocumentCode
1591691
Title
A Hybrid Optimization Method Based on Cellular Automata and its Application in Soft-Sensing Modeling
Author
Xu, Yufa ; Chen, Guochu ; Yu, Jinshou
Author_Institution
Shanghai DianJi Univ., Shanghai
Volume
3
fYear
2007
Firstpage
231
Lastpage
235
Abstract
By studying cellular automata, a new optimization method based on cellular automata is proposed by this paper. The new optimization method assumes that "life game" are applied in operator of genetic algorithm (GA). Experiment results show that the new method has good optimization performance. Then, a hybrid neural network algorithm based on life game, GA and back-propagation algorithm is presented to train soft-sensing model of acrylonitrile yield. Experiment results show that the hybrid soft sensing model proposed in this paper has good performance and high measuring precision.
Keywords
backpropagation; cellular automata; genetic algorithms; neural nets; acrylonitrile yield; backpropagation algorithm; cellular automata; genetic algorithm; hybrid optimization; life game; neural network; soft-sensing modeling; Artificial neural networks; Automation; Biology; Cells (biology); Cellular neural networks; Computer science; Genetic algorithms; Neural networks; Optimization methods; Pattern recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location
Haikou
Print_ISBN
978-0-7695-2875-5
Type
conf
DOI
10.1109/ICNC.2007.53
Filename
4344512
Link To Document