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DOBD Algorithm for Training Neural Network: Part II. Application 被引量:1

DOBD Algorithm for Training Neural Network: Part II. Application
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摘要 In the first part of the article, a new algorithm for pruning networkDynamic Optimal Brain Damage(DOBD) is introduced. In this part, two cases and an industrial application are worked out to test the new algorithm. It is verified that the algorithm can obtain good generalization through deleting weight parameters with low sensitivities dynamically and get better result than the Marquardt algorithm or the cross-validation method. Although the initial construction of network may be different, the finial number of free weights pruned by the DOBD algorithm is similar and the number is just close to the optimal number of free weights. The algorithm is also helpful to design the optimal structure of network. In the first part of the article, a new algorithm for pruning networkDynamic Optimal Brain Damage(DOBD) is introduced. In this part, two cases and an industrial application are worked out to test the new algorithm. It is verified that the algorithm can obtain good generalization through deleting weight parameters with low sensitivities dynamically and get better result than the Marquardt algorithm or the cross-validation method. Although the initial construction of network may be different, the finial number of free weights pruned by the DOBD algorithm is similar and the number is just close to the optimal number of free weights. The algorithm is also helpful to design the optimal structure of network.
出处 《过程工程学报》 CAS CSCD 北大核心 2002年第3期262-267,共6页 The Chinese Journal of Process Engineering
关键词 DOBD算法 人工神经网络 应用研究 neural network DOBD algorithm Marquardt method overfitting pruning training application
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参考文献5

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