| 基于L-M优化神经网络算法的地下水动态模拟与预测 |
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| 引用本文： | 常亮,解建仓,王少波,肖志娟.基于L-M优化神经网络算法的地下水动态模拟与预测[J].地下水,2005,27(5):380-383. |
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| 作者姓名： | 常亮 解建仓 王少波 肖志娟 |
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| 作者单位： | 西安理工大学,陕西,西安,710048 |
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| 摘 要： | 本文根据地下水与其影响因素之间存在的非线性映射关系,在BP网络模型的基础上,提出一种Levenberg-Marquart优化神经网络算法,并将其应用于某地地下水的动态模拟与预测.通过与BP算法的仿真结果比较分析,发现该算法稳定性好,收敛速度快,预测精度高.
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| 关 键 词： | 地下水动态 神经网络 Levenberg-Marquart算法 |
| 文章编号： | 1004-1184（2005）05-0380-04 |
| 收稿时间： | 2005-06-21 |
| 修稿时间： | 2005-06-21 |
The Simulation and Prediction of Groundwater Regime based on the Optimized Algorithm of L-M Neural Network |
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| CHANG Liang,XIE Jiancang,WANG Shaobo,XIAO Zhijuan.The Simulation and Prediction of Groundwater Regime based on the Optimized Algorithm of L-M Neural Network[J].Groundwater,2005,27(5):380-383. |
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| Authors: | CHANG Liang XIE Jiancang WANG Shaobo XIAO Zhijuan |
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| Institution: | Xian University of Science and Technology Xian, Shaanxi 710048 |
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| Abstract: | The pape is according to the nonlinear relationship between groundwater and its influenced factors, a Levenberg-Marquart optimized algorithm of BP neural network is proposed, and applied for the simulation and prediction of groundwater regime in some area. Through the analysis of simulation results as compared with BP algorithm, this algorithm has the advantages of fine stability, fast convergence speed and high precision. |
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| Keywords: | groundwater regime neural network Levenberg-Marquart algorithm |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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