System Identification Based on Mixed Immune Neural Networks
To the problem that exists in the traditional identification methods and the neural network method, a new neural network identification method based on a mixed immune optimization algorithm is presented, and applied in the identification of placing process of chip Mounters components. The results of simulation show that the method is effective. It can not only avoid the traditional neural network easily to fall into the partial extreme values shortcoming, compared with the traditional genetic arithmetic and basic immune algorithm, but also improve its convergence rate and accuracy.
Yanqiu Wang Yueling Zhao Yu Wang Le Liu
College of Information Science and Engineering Liaoning University of Technology Jinzhou,121001 P.R.China
国际会议
南宁
英文
2007-07-20（万方平台首次上网日期，不代表论文的发表时间）