An improved counter propagation networks and its application
Niu Da · Journal of Central South University(Science and Technology) · 2008
Based on the fact that the input vectors of counter propagation networks(CPN) are supposed to be uniform distribution,,and it is difficult to choose the number of their hidden lay neurons,its application is restricted in a few fields,CPN algorithm was improved and was applied to power load forecasting.The results show that through changing the setting rules of the initiation weight,the problem of too strict limitation to input vectors can be solved.Based on the optimization of the operation process,the efficient of the CPN can be enhanced.The simulation error using the ameliorated CPN is lower than those with BP,RBF and Elman networks.Compared to traditional BP networks,the forecasting accuracy using the ameliorate ameliorated PN improves about 4%,and the computing time reduces 45%.The improved CPN can be used to forecast the power load.