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| An Improved BP Algorithm and Its Application in Classification of Surface Defects of Steel Plate |
| ZHAO Xiang��yang1,LAI Kang��sheng2,DAI Dong��ming2 |
| 1. Research and Development Division, Haier Group, Qingdao 266101, Shandong, China; 2. Department of Physics, Dalian University of Technology, Dalian 116024, Liaoning, China |
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Abstract 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.
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Received: 01 January 1900
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2007, Vol. 14 
