摘要
论述了遗传算法－优化设计－神经网络的耦合技术。以一台机器的主控制参数作为样本，采用这种耦合技术，将实际工程参数转化为遗传进化样本，再通过优化技术变成最优样本，来训练神经网络系统，旨在提高控制参数质量。
Combination technology on genetic algorithms、 optimum technology and neural networks are analysed and presented. The main control parameters of pressure pour pulp casting machines are discussed as an example. Using combination technology, the sample of the main control parameter is changed to a genetic sample. Using the optimum technology again, the genetic sample is converted to the optimum sample. The neural network system is obtained by the optimum sample. This increasing quality of engineering main control parameters is designed.
关键词
耦合技术
遗传算法
神经网络
优化设计
combination technology
genetic algorithms
neural networks
