| 大坝渗流场转异时效计算的神经网络法 |
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| 引用本文： | 张乾飞 张秋野. 大坝渗流场转异时效计算的神经网络法[J]. 水电能源科学, 2005, 23(3): 62-64,i006 |
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| 作者姓名： | 张乾飞 张秋野 |
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| 作者单位： | 1. 上海市政工程设计研究院,上海,200092;上海交通大学,船舶海洋与建筑工程学院,上海,20030
2. 河海大学,土木工程学院,江苏,南京,210098 |
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| 基金项目： | 国家自然科学基金重点资助项目(50139030) |
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| 摘 要： | 依据神经网络独特的非线性映射能力，建立了反映环境量与大坝渗流要素之间关系的神经网络模型，推导了反映复杂渗流场演变规律的时效分量及其时间导数，由此建立了大坝渗流场转异时效计算的神经网络法。最后通过实例验证，并与回归分析法比较，结果表明该方法与回归分析法的结果相吻合。
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| 关 键 词： | 大坝渗流场 转异时效 神经网络 回归分析 |
| 文章编号： | 1000-7709(2005)03-0062-03 |
Neural Network Method for Abstracting Mutational Time-effect of Dam Seepage Flow Field |
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| ZHAGN Qianfei. Neural Network Method for Abstracting Mutational Time-effect of Dam Seepage Flow Field[J]. International Journal Hydroelectric Energy, 2005, 23(3): 62-64,i006 |
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| Authors: | ZHAGN Qianfei |
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| Abstract: | According to the strong nonlinear mapping ability of n eural network, neural network model characterizing the relationship between dam seepage flow field and surroundings variables is established. Consequently, the time-effect component and its derivative are deduced according to the neural ne twork model, and the neural network method is constructed foring mutati onal time-effect. Finally, the method is applied into a case study and it shows feasibility and effectiveness through comparison with the result from regressio n analysis and the results show consistency with the traditional method. |
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| Keywords: | dam seepage flow field mutational time-effect neural network method regression analysis |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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