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
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;
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
DOI :
10.1109/ICNC.2007.53
