An Improved BP Algorithm and Its Application in Classification of Surface Defects of Steel Plate

作     者：ZHAO Xiang-yang LAI Kang-sheng DAI Dong-ming 

作者机构：Research and Development Division Haler Group Qingdao 266101 Shandong China Department of Physics Dalian University of Technology Dalian 116024 Liaoning China 

出 版 物：《Journal of Iron and Steel Research International》 (JOURNAL OF IRON AND STEEL RESEARCH INTERNATIONAL)

年 卷 期：2007年第14卷第2期

页      面：52-55页

核心收录：

学科分类：080503[工学-材料加工工程] 0806[工学-冶金工程] 08[工学] 0805[工学-材料科学与工程（可授工学、理学学位）] 0703[理学-化学] 0802[工学-机械工程] 0702[理学-物理学] 0801[工学-力学（可授工学、理学学位）] 080201[工学-机械制造及其自动化] 

基　　金：Item Sponsored by National Natural Science Foundation of China (60277029) 

主　　题：artificial neural network MLP BP algorithm SVD generalized inverse matrix 

摘      要：Artificial neural network is a new approach to pattern recognition and classification. The model of multilayer perceptron （MLP） and back-propagation （BP） is used to train the algorithm in the artificial neural network. An improved fast algorithm of the BP network was presented, which adopts a singular value decomposition （SVD） and a generalized inverse matrix. It not only increases the speed of network learning but also achieves a satisfying precision. The simulation and experiment results show the effect of improvement of BP algorithm on the classification of the surface defects of steel plate.