基于模式相关的改进BP神经网络算法  

Improved BP Neural Network Algorithm Based on Mode Correlation

作　　者：谢永成[1] 董今朝[2] 李光升[2] 魏宁[2] 

机构地区：[1]装甲兵工程学院外训系,北京100072 [2]装甲兵工程学院控制工程系,北京100072

出　　处：《计算机系统应用》2013年第12期100-103,99,共5页Computer Systems & Applications

摘　　要：针对传统的BP神经网络模式分类算法在各个网络输出值较为接近或者模式类之间的网络输出值接近的情况下容易发生误判的问题,提出一种基于模式相关的BP神经网络分类算法,并结合具体电路,运用该方法进行建模、仿真.实验结果表明,采用模式相关的BP神经网络分类算法能够充分利用网络输出层各个节点的所有输出,增强了网络的输出特性,便于正确、方便的进行模式分类,且分类效果良好,具有一定的通用性.The traditional BP neural network classification algorithm has the inherent shortcomings such as miscarriage of justice when each network＇s output value or network output value between the mode classes is similar. So the fault diagnosis method of BP neural network based on mode correlation is proposed. Then the modeling and simulation are performed with a specific circuit. Experimental results show that the BP neural network which combining with mode correlation has made full use of all of the value which is outputted by every node of the network output layer and strengthened the network output performance. This method has made mode classification more convenient, better classification results and has certain universality..

关 键 词：BP神经网络 模式相关 故障诊断 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]