Method for association rule mining of ocean-land climate events with combination of climate subdivision thought

Abstract

The invention discloses a method for association rule mining of ocean-land climate events with combination of a climate subdivision thought. A Delaunay triangulation network of space data is established and an overall and local long-side constraint is exerted on the space data, so that a reasonable and stable space adjacent relation network is obtained, the similarity of a time series of space adjacent entities is measured, hierarchical clustering is conducted to obtain a hierarchical cluster result, and a good climate subdivision result is obtained on the basis of false-T statistical magnitude analysis; a prior knowledge constraint of a related field is brought in and interested climate events are extracted from ocean climate indexes and land climate zones respectively, so that effective association rules among the ocean-land climate events are mined through exertion of a time window width constraint, a time delay constraint and a sufficiency and necessity constraint. The multi-scale effect can be effectively considered in the mining process so that an effective climate zone can be obtained and high efficiency, pertinence and practicability can be achieved through multiple constraints when the association rules are mined.

Description

Technical field [0001] The invention relates to the technical field of spatio-temporal data mining and analysis, in particular to a method for mining association rules of sea and land climate events that integrates the idea of ​​climate zoning. Background technique [0002] In recent years, global climate change has led to frequent occurrences of abnormal climate events, which has a serious negative impact on human living environment and economic development. Studies have shown that ocean climate abnormalities have an important inducing effect on terrestrial climate abnormal events. Land and sea climate data usually record the changing trends of sea and land climate elements over time in the form of time series. It has the characteristics of massive, multidimensional, and heterogeneous, and contains a large number of unknown sea and land climate related models. [0003] Many scholars have done a lot of research in order to discover the hidden correlation patterns between sea and la...

AI Technical Summary

Problems solved by technology

[0004] The technical problem to be solved by the present invention is to solve the technical problems encountered in the mining of association rules of sea and land climate events in view of the defects of the existing technology

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