A Hybrid Optimization Method Based on Cellular Automata and its Application in Soft-Sensing Modeling
Yufa Xu, Guochu Chen, Jinshou Yu · 2007
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.