Research on Neural Network Integration Fusion Method and Application
Zhao Hai · Jisuanji gongcheng · 2007
A new fusion model is proposed,which is the combination of integration BP neural networks models and DS evidence reasoning model,to solve the problems of low precision rate in automotive engine fault diagnosis by traditional expert system.The method of this paper not only realizes feature level fusion of all subjective observation data and expert experiments on different parts of engineer,but also realizes the predominance compensation of different models.In simulation experiment,by comparison between the two methods,this method proposed can improve diagnosis precision by 7.1% while reduces time and complexity.