河型自然分类的河流模糊等价矩阵聚类方法  

Natural classification of river patterns based on clustering method with fuzzy equivalent matrices

作　　者：史传文[1] 吴保生[2] 马吉明[2] 

机构地区：[1]黄河水利职业技术学院,开封475003 [2]清华大学水沙科学与水利水电工程国家重点实验室,北京100084

出　　处：《水力发电学报》2009年第5期215-220,133,共7页Journal of Hydroelectric Engineering

基　　金：河南省自然科学基金(0224050021)

摘　　要：任意一种河型的河流集合都是河流模糊集合,河型之间的关系为模糊关系,由此建立了冲积河流河型自然分类的河流模糊等价矩阵聚类方法。该方法应用了河型成因的输沙平衡程度理论假说和输沙平衡程度公式。利用黄河下游20年资料的计算结果表明,采用该方法可以有效地对冲积河流河型进行自然分类和预测。根据河型自然分类结果,对不同河型的输沙平衡程度数集合进行分析,可以揭示河型之间的本质联系与区别。This paper assumes that any set of fiver pattems can be considered as a fuzzy fiver set and that the relation between river patterns is a fuzzy relation. From this concept, a method for natural classificaiton of river patterns based on clustering method with fuzzy equivalent matrices is proposed. The method is based on the hypothesis and formula of equilibrium degree of sediment transport for the alluvial river patterns. Test based on 20 years＇ data of the Yellow River show that the channel patterns can be well distinguished and predicted by the proposed method. The clustering results can effectively reveal the relation and difference between fiver patterns.

关 键 词：河床演变 自然分类 模糊等价矩阵 河型 

分 类 号：TV143[水利工程—水力学及河流动力学]