计算机与数字工程2019，Vol.47Issue(5)：1037-1041,5.DOI:10.3969/j.issn.1672-9722.2019.05.005
改进的BP神经网络算法的研究与应用
Research and Application of Improved BP Neural Network Algorithm
摘要
Abstract
In order to solve the problem that the convergence speed of BP algorithm is slow and the local minimum value is easy to fall into the local minimum value,in improving the fast problem and stability of the neural network algorithm,the existing improved BP algorithm still has some imperfections. In this paper,the BP algorithm integrates the advantages of the genetic algo?rithm and changes into the compressed mapping genetic and the BP neural network. An algorithm for combining advantages. As the improved BP algorithm integrates the principle of compression mapping,it can help solve the slow convergence rate in the process of using the algorithm,and the algorithm can easily fall into the local minimum in the use of the algorithm. The improved BP algorithm will enhance the convergence speed of BP network structure,and will make up for the traditional defects of BP neural network. Com?pared with the traditional BP algorithm,the improved BP algorithm reduces the number of training steps and saves the training time. And through data experiment,it is feasible to apply the improved algorithm to practice.关键词
神经网络/压缩映射/优化/权值Key words
neural network/compression mapping/optimization/weight分类
信息技术与安全科学引用本文复制引用
富宇,李倩,刘澎..改进的BP神经网络算法的研究与应用[J].计算机与数字工程,2019,47(5):1037-1041,5.基金项目
黑龙江省自然科学基金项目(编号:F2015020)资助. （编号:F2015020）
