Meteorological Data Mining Based on Rough Set Attributes Reduction and Decision Tree

Xiao Ling Li; Xu Wang

doi:10.4028/www.scientific.net/AMM.556-562.3388

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 556-562Meteorological Data Mining Based on Rough Set...

Meteorological Data Mining Based on Rough Set Attributes Reduction and Decision Tree

Abstract:

With the development of society and economy, meteorological information service has been paid more and more attention. Furthermore, frequent extreme weather because of the environmental deterioration makes the accurate and efficient weather forecast more and more important. However, the characteristic of huge amount of meteorological data leads to the difficulty of analysis. The analysis of meteorological data based on data mining technique is a research hotspot currently. This paper analyses the weather elements using the method of rough set attributes reduction, which can remove a portion of factors that can be ignored in the analysis of rainfall possibility, and improves the efficiency of meteorological analysis and decision making using decision tree.

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Periodical:

Applied Mechanics and Materials (Volumes 556-562)

Pages:

3388-3391

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.556-562.3388

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Online since:

May 2014

Authors:

Xiao Ling Li*, Xu Wang

Keywords:

Attribute Reduction, Decision Tree, Meteorological Data Mining, Rough Set (RS)

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* - Corresponding Author

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