摘要
基于时间序列多重信息利用的扩维原理和灰色系统理论的关联分析思想,提出一种应用于水文中长期预报的方法。它的特点是直接从径流序列的扩维相型关联分析中,寻求径流情势变化规律,较适合于缺乏输入因子资料或选择影响因子有困难条件下的水文中长期预报。利用海河、黄河和长江流域若干水文站的实测资料序列对该方法做了初步验证。
This paper addresses the problem of mid-long term runoff forecasting. An extended dimension approach from one dimension to multiple dimensions in hydro-logical time series was developed in terms of the idea of pooling hydrological information from different sources whereby historical data were used to form a family of runoff pattern and a set of corresponding forecasting vector. A workable and practical method called as the grey correlative pattern recognition was developed to determine a most similar hydrological pattern and forecast runoff in the leading time. Eight catchments under different climate conditions in the basins of the Yellow River and the Yangtze River were selected for verifying annual and monthly runoff forecasting. It was found that the proposed method yields a better runoff forecasting than the AR (p) model.
出处
《水科学进展》
EI
CAS
CSCD
1993年第3期190-197,共8页
Advances in Water Science
基金
国家自然科学基金青年基金和水利部资助项目
关键词
径流
长期预报
模式识别
中期预报
Runoff
Forecast
Pattern recognition
Grey correlative analysis.