A method for distinguishing similarity of middle and small river basin

Abstract

A method for distinguish similaritying of middle and small river basin includes such steps: constructing a dataset clustering collective; selecting characteristic index to construct characteristic subset, inputting the characteristic subset into basic clustering algorithm to obtain a clustering subset; constructing the similarity matrix of the clustering collectivity; using the similarity matrix of the clustering collectivity as the input matrix of the preset clustering fusion algorithm; finally, performing matrix clustering fusion: using the preset clustering fusion algorithm to perform clustering fusion of the similarity matrix to realize similarity judgment. The invention fully utilizes the characteristics of the geographic data and the hydrological data of the small and medium-sized watershed, and realizes similarity analysis of the small and medium-sized watershed by using the data mining technology, so as to solve the technical problem that the similarity of the hydrological watershed is difficult to be judged.

Description

technical field [0001] The invention belongs to the technical field of data mining, and in particular relates to a method for discriminating the similarity of small and medium river basins. Background technique [0002] In my country, flood is one of the natural disasters with the highest probability of occurrence and the most serious damage. At present, my country's management of major rivers has tended to be perfect, and the huge investment in embankments, river courses and dam reservoirs has provided a solid foundation for my country's flood control. However, small and medium-sized watersheds will also have large or small flood disasters after heavy rain or heavy rain. Compared with large rivers, many small and medium-sized watersheds have not received enough attention in terms of flood control. According to incomplete statistics, there are more than 50,000 small and medium-sized river basins in China, and 85% of the cities in my country are located along the coast of th...

AI Technical Summary

Problems solved by technology

However, at this stage, the similarity analysis of small and medium watersheds mainly relies on manual analysis, and there is no complete automatic analysis model

[0004] Nowadays, the analysis and determination of similar watersheds basically rely on the human decisions of hydrologists. This analysis method has many unobjective and inaccurate situations

At the same time, the process of watershed similarity analysis using purely hydrological methods also contains a lot of uncertainty, so it is difficult to conduct quantitative similarity analysis of watersheds through common deterministic methods

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