摘要
提出了一种快速收敛Ｂ－Ｐ网学习算法，并将其用于离线调优控制。详细讨论了神经网络调化模型的实现原理和过程，并对Ｄ３０５丙烯精馏塔进行了仿真调优控制，仿真结果表明了本方法的有效性。
A B-P algorithm of fast convergency was proposed and used to the offline optimization control. The realized principle and procdure of neural network optimization model was discussed in detail and the . simulation optimization control to D305 propylene recifying tower was done, the simulation result indicated.the . efficiency of method.
出处
《抚顺石油学院学报》
1997年第1期59-61,共3页
Journal of Fushun Petroleum Institute
关键词
神经网络
离线调优
精馏塔
石油化工
Neural networks: Offline optimization control
B -P algorithm Rectifying towers
