| 神经网络自调节变尺度算法及其用于聚酯生产工况预测 |
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| 引用本文： | 杨秋贵,张素贞.神经网络自调节变尺度算法及其用于聚酯生产工况预测[J].华东理工大学学报(自然科学版),1997,23(1):89-94. |
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| 作者姓名： | 杨秋贵 张素贞 |
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| 作者单位： | 华东理工大学自控系 |
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| 基金项目： | 国家“八·五”科技攻关项目 |
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| 摘 要： | 探讨了多层前向神经网络的学习算法，并将该算法用于大型聚酯生产工况预测。结合非线性最优化方法，提出了一种基于拟牛顿法的神经元网络自调节变尺度学习算法，仿真结果表明，该算法有效地改进了神经元网络学习收敛速度和收敛性能。
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| 关 键 词： | 神经网络 聚酯 自调节变悄度 拟牛顿法 工况 |
Learning Algorithm with Self scaling Variable Metric for Neural Networks and Its Application for Predicting the Conditions of Polyethylene Terephthalate |
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| Yang Qiugui,Zhang Jie and Zhang Suzhen.Learning Algorithm with Self scaling Variable Metric for Neural Networks and Its Application for Predicting the Conditions of Polyethylene Terephthalate[J].Journal of East China University of Science and Technology,1997,23(1):89-94. |
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| Authors: | Yang Qiugui Zhang Jie and Zhang Suzhen |
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| Institution: | Yang Qiugui,Zhang Jie and Zhang Suzhen * |
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| Abstract: | In a complex chemical industry process, predicting the conditions of the process is one of the most promising fields for neural networks application. This paper is concerned with improvements of neural networks learning algorithm and its application for predicting the production conditions of polyethylene terephthalate (PET). On the basis of the analysis of the optimization methods, a new algorithm based on Quasi newton method with self scaling variable metric is proposed. Simulation results show the effectiveness and the good convergence of the new algorithm. |
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| Keywords: | neural networks artificial intelligence Quasi newton polyethylene terephthalate self scaling variable metric |
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