| BP网络应用于黄河水质浓度的预测研究 |
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| 引用本文： | 陈丽华.BP网络应用于黄河水质浓度的预测研究[J].西北民族学院学报,2003,24(1):39-43. |
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| 作者姓名： | 陈丽华 |
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| 作者单位： | 西北民族学院化学系 甘肃兰州730030 |
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| 摘 要： | 我们首次建立了不同算法运用于DO浓度预测的三种BP神经网络模型 ,并将其用于地表水质浓度的预测 结果表明 ,三种网络均可较满意地预测DO浓度 但比较之下 ,基于L -M改进算法的BP网络在非线性时间序列DO值的预测中显示出了独特的优越性
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| 关 键 词： | B-P传统算法 动量-自适应调整算法 Levenberg-Marpuardt算法 溶解氧(DO) |
| 文章编号： | 1009-2102(2003)01-0039-05 |
| 修稿时间： | 2002年10月25 |
Based of Three Algorithms of BP Neutral Networks to Predict Groundwater' DO Concentration |
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| CHEN Li,hua.Based of Three Algorithms of BP Neutral Networks to Predict Groundwater'''' DO Concentration[J].Journal of Northwest Minorities University(Natural Science ),2003,24(1):39-43. |
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| Authors: | CHEN Li hua |
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| Abstract: | Three BP network models for prediction of DO concentration were set up and used to predict the observation data of grou ndwater concentration for the first time. The results showed that predicted and observed values were all in relatively good agreements. But among the three mode ls, a BP network model based on Levenberg-Marpuardt algorithm was special advan tageous to predict nonlinear time series of DO values. |
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| Keywords: | Back-Propagation algorithm Momentum-learning coeffi cient adjustment algorithm Levenberg-Marpuardt algorithm DO |
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