摘要
针对某轧钢厂的热连轧产品质量生产过程,对遗传算法(GA)的交叉和变异操作进行改进,给出了基于改进的遗传算法(IGA)优化小波神经网络(WNN)结构的产品质量建模方法。仿真实例表明:该建模方法既保留了GA的全局搜索能力和WNN学习算法简单有效的特点,又具有网络训练速度快、建模精度高等优点,表明了该方法的有效性。
Aiming at the quality production process of Hot Rolling Mill products of a rolling mill,the crossover and mutation operations of GA get improved,then a products quality modeling method based on the WNN optimized by IGA is presented.Simulation results show that the quality modeling method not only maintains the features of global searching ability of GA and the simplicity and effectiveness of WNN learning algorithm,but also has the advantages of the fast network training speed and the high modeling precision,and then the effectiveness of the proposed method is indicated.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第16期210-212,共3页
Computer Engineering and Applications
基金
河南省杰出青年计划项目(No.084100510009)~~
关键词
轧钢生产过程
产品质量建模
遗传算法
小波神经网络
steel rolling production process
products quality modeling
Genetic Algorithm（GA）
Wavelet Neural Network（WNN）
