Research on BP Neural Network Algorithm Based on Quasi- Newton Method

作     者：Lu Peixin 

作者机构：Eastcom BUPT Information Technology Co.LTD. Beijing 100191 

出 版 物：《International Journal of Technology Management》 (国际技术管理)

年 卷 期：2014年第7期

页      面：71-74页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 081104[工学-模式识别与智能系统] 08[工学] 070105[理学-运筹学与控制论] 0835[工学-软件工程] 0701[理学-数学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Newton method BP neural network improved algorithm 

摘      要：With more and more researches about improving BP algorithm, there are more improvement methods. The paper researches two improvement algorithms based on quasi-Newton method, DFP algorithm and L-BFGS algorithm. After fully analyzing the features of quasi- Newton methods, the paper improves BP neural network algorithm. And the adjustment is made for the problems in the improvement process. The paper makes empirical analysis and proves the effectiveness of BP neural network algorithm based on quasi-Newton method. The improved algorithms are compared with the traditional BP algorithm, which indicates that the imoroved BP algorithm is better.