| 基于智能算法的地下水位动态预测模型的建立与应用 |
| |
| 引用本文： | 刘勇健.基于智能算法的地下水位动态预测模型的建立与应用[J].水文地质工程地质,2004,31(3):55-57,61. |
| |
| 作者姓名： | 刘勇健 |
| |
| 作者单位： | 广东工业大学,广州,510643 |
| |
| 基金项目： | 广东省自然科学基金项目资助(20010054)，广东工业大学重点学科基金(20216) |
| |
| 摘 要： | 地下水系统是一个高度复杂系统,地下水位与其影响因素之间存在非线性映射关系。本文分析了BP神经网络的缺陷和遗传算法的特点,根据区域水文特征,提取了地下水位的主要影响因子,建立了基于GA和BP的地下水动态预测模型,并应用于某水源地的地下水位动态预测中。结果表明,该模型收敛快、预测精度高,具有良好的推广应用前景。
|
| 关 键 词： | 智能算法 遗传算法 人工神经网络 地下水位 动态预测 |
| 文章编号： | 1000-3665(2004)03-0055-03 |
The establishment and application of dynamic prediction model of groundwater level based on intelligent algorithm |
| |
| LIU Yong-jian.The establishment and application of dynamic prediction model of groundwater level based on intelligent algorithm[J].Hydrogeology and Engineering Geology,2004,31(3):55-57,61. |
| |
| Authors: | LIU Yong-jian |
| |
| Abstract: | Underground water system is a highly complex one. There is a nonlinear relationship between underground water level and its major influential factors. This paper analyzes the shortcoming of BP neural networks and the characteristic of genetic algorithm. On the basis of the hydrologic characteristic, the major factors concerning underground water level are derived, and a dynamic prediction model of underground water level is built, which is used in a specific water resource spot. The case study shows that the model has quick convergence speed and high prediction precision as well as wide practicability in the engineering. |
| |
| Keywords: | intelligent algorithm genetic algorithm artificial neural networks underground water level dynamic prediction |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
