局部式反传网络的改进BP算法及应用

针对标准BP算法收敛速度慢的缺点，分析了其产生的主要原因，提出了一种改进BP算法。在传统BP算法基础上通过对其激励函数增加陡度因子并在误差反传权值修正时增加协调器，通过对网络灵敏度的分析将全反传式网络变成局部式反传网络，从而达到提高网络学习速率及精度的目的。改进的BP算法应用于导向钻井稳定平台系统的辨识，仿真结果表明该算法收敛速度快，精度高。

BP algorithm based on partial counter propagation network and its application

According to the shortcomings of slow convergence of the standard BP （Back-Propagation） algorithm, its main causes are analyzed and the improved algorithm of BP algorithm with the partial counter propagation network is proposed. Through increasing steepness factor of activation ftmctions and increasing coordinator to modify weights when the error is in the back propagation, a full back-propagation type network becomes local-style back-propagation network by means of the analysis of the sensitivity of the net- work, so as to achieve the purpose of enhancing the learning speed and accuracy. Improved BP algorithm is applied to identification of the stable platform on steerable drilling system. Simulation comparison results show that, in a given accuracy requirement and its convergence speed, this improved BP neural network is superior to traditional BP network, so it has Rood research and application value.