Classification of Data Mining Techniques for Weather Prediction

Jaswant Meena¹ , Ashish Mandloi²

Section:Research Paper, Product Type: Isroset-Journal
Vol.4 , Issue.1 , pp.21-24, Feb-2016

Online published on Apr 01, 2016

Copyright © Jaswant Meena, Ashish Mandloi . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Weather forecasting is critically important application in meteorology and has been one of the most scientifically and technologically challenging problem through out the globe since past and still only approximations are being made to accurate prediction of weather eventslike cloudburst,hailingetc. Machine learning algorithms are implemented in data mining process to extract hidden patterns and useful information from huge weather databases, essential to get prepare for the worst of the ambience. This paper propounds the comparative analysis of various data mining techniques applied by different researchers in different domains. This survey also reviews the available literatures of algorithms applied by different researchers to exploit various data mining techniques for detecting and predicting weather events. For weather prediction Decision Tree, Artificial Neural Network and SVM techniques gives better results with high prediction accuracy than other data mining techniques for multidimensional weather data sets.

Key-Words / Index Term :
Data mining; Decision Tree; Hailstorm; Machine Learning; Multilayer Perceptron; Support Vector Machine

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