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| 典型下垫面径流系数预测的神经网络方法研究 | |
| 引用本文： | 武晟,解建仓,汪志荣,黄铎,汪雅梅.典型下垫面径流系数预测的神经网络方法研究[J].环境科学与技术,2007,30(5):1-2,5. |
| 作者姓名： | 武晟 解建仓 汪志荣 黄铎 汪雅梅 |
| 作者单位： | 1. 西安理工大学水资源研究所,西安,710048 2. 天津理工大学环境科学与安全工程学院,天津,300191 3. 西安理工大学管理学院,西安,710048 |
| 基金项目： | 国家自然科学基金 , 国家自然科学基金 , 国家高技术研究发展计划(863计划) |
| 摘 要： | 根据5种典型下垫面的径流系数的实测数据,运用LM(Levenberg-Marquardt)BP算法的神经网络模型,建立了径流系数与影响因素关系间的S型/S型数学模型。用该方法对不同降雨条件下每种下垫面的径流系数进行了预测,并与传统方法进行了比较。结果表明,该模型的预测精度更高。 |
| 关 键 词： | 神经网络 径流系数 降雨强度 雨水利用 |
| 文章编号： | 1003-6504（2007）05-0001-03 |
| 修稿时间： | 2006-03-312006-06-07 |
Runoff Coefficient Forecast of Typical Underlying Surface Based on Neural Network Method |
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| WU Sheng,XIE Jian-cang,WANG Zhi-rong,HUANG Duo,WANG Ya-mei.Runoff Coefficient Forecast of Typical Underlying Surface Based on Neural Network Method[J].Environmental Science and Technology,2007,30(5):1-2,5. | |
| Authors: | WU Sheng XIE Jian-cang WANG Zhi-rong HUANG Duo WANG Ya-mei |
| Abstract: | Based on measured data of five typical underlying surfaces,S/S mathematical model of relationship between different underlying surfaces and influence factors were developed by using LM calculation method.The runoff coefficient of every underlying surface was forecasted in different rainfall conditions by ANN models and compared with conventional method as well.Result showed that the ANN models improved the precision of forecast. |
| Keywords: | neural network runoff coefficient rainfall intensity rainwater utilization |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |