基于模糊集合理论和集对原理的径流丰枯分类方法  

Approach to annual runoff classification based on fuzzy set theory and set pair analysis

作　　者：丁小玲[1,2] 周建中[1,2] 陈璐[1,2,3] 赵云发[4] 李晖[4] 

机构地区：[1]华中科技大学水电与数字化工程学院,武汉430074 [2]数字流域科学与技术湖北省重点实验室,武汉430074 [3]Department of Biological and Agricultural Engineering & Zachry Department of Civil Engineering, Texas A&M University, College Station [4]中国长江三峡集团公司三峡梯调中心,湖北宜昌443002

出　　处：《水力发电学报》2015年第5期4-9,共6页Journal of Hydroelectric Engineering

基　　金：国家自然科学基金重点项目(51239004).;高等学校博士学科点专线科研基金资助项目(20100142110012)

摘　　要：在分析现有基于集对分析的年径流丰枯分类方法不足的基础上,考虑径流等级划分的模糊性和径流的年内分布特性,提出模糊化径流分级标准,并引入基于径流分布的年内丰枯贡献权重因子,得到年径流对于各个等级的综合隶属度,进而利用集对分析方法判断年径流的丰枯等级。利用所提方法对溪洛渡径流丰枯等级进行分析,结果表明该方法较于单一的集对分析方法能更好的描述径流丰枯状态。To consider fuzziness in river runoff, an improved method for annual runoff classification and a fuzzy classification criteria of runoff are presented by analyzing the existing classification approach based on set pair analysis. We adopted a contribution weighting factor to describe both the annual amount of runoff and its features of distribution in a year, and obtained a comprehensive membership degree of annual runoff for each class. Then, we evaluated and classified the annual runoff level relative to high and low flows using a set pair analysis method. Application to the runoff analysis of the Xiluodu station at the Jinsha River shows that this method is more effective in runoff level classification than approaches based on set pair analysis.

关 键 词：水文学 年径流分类 模糊集合 集对分析 溪洛渡 丰枯贡献权重 

分 类 号：K312[历史地理—历史学]