• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>World Engineers' Convention 2004 vol F-A: Resources and Energy; 20041102-06; Shanghai(CN) >Component Disassembled Forecasting Method of Hydrologic Time Series Based on Maximum Entropy Spectra Analysis (MESA)
【24h】

Component Disassembled Forecasting Method of Hydrologic Time Series Based on Maximum Entropy Spectra Analysis (MESA)

机译：基于最大熵谱分析的水文时间序列分量分解预测方法

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The component analysis is a considerable important issue in the investigation of the mechanism of hydrologic series, as well as the base of hydrologic simulation and forecasting. Informational entropy, especially the Principle of Maximum Entropy (POME) and Maximum Entropy Spectra Analysis (MESA), have been successfully and widely applied in a good many research fields, including hydrology and water resources. Based on the component analysis of hydrologic time series, a new method, named the component disassembled forecasting method with the integration of Maximum Entropy Spectra Analysis (MESA) is developed here. Hydrologic time series is considered to be composed with deterministic component, which includes non-periodic one and periodic one, and the stochastic component. And they are identified and represented according to themselves' natural characteristic. MESA is used to detect the cryptic period characteristics, which mean the deterministic periodic component, and to compute the coefficients of the stochastic model selected. The forecasting of annual runoff series, monthly runoff series, and maximum flood peak series of Huanyuankou Station in the Yellow River is used as the case to illustrate and validate this method.
机译：成分分析是研究水文序列机理的重要问题，也是水文模拟预报的基础。信息熵，特别是最大熵原理（POME）和最大熵谱分析（MESA），已经成功地广泛应用于包括水文和水资源在内的许多研究领域。在水文时间序列成分分析的基础上，提出了一种结合最大熵谱分析（MESA）的成分分解预测方法。水文时间序列被认为是由确定性成分组成的，其中包括非周期性的一个和周期性的成分，以及随机性的成分。并根据自身的自然特征对其进行识别和表示。 MESA用于检测隐含的周期特性，这意味着确定性的周期性成分，并计算所选随机模型的系数。以黄河Hua源口站年径流量系列，月径流量系列和最大洪峰系列预报为例，说明和验证了该方法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号