Comparison between J48 Decision Tree, SVM and MLP in Weather Forecasting

International Journal of Computer Science and Engineering
© 2016 by SSRG - IJCSE Journal
Volume 3 Issue 11
Year of Publication : 2016
Authors : Suvendra Kumar Jayasingh, Jibendu Kumar Mantri, P. Gahan
: 10.14445/23488387/IJCSE-V3I11P109

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Citation:
MLA Style:

Suvendra Kumar Jayasingh, Jibendu Kumar Mantri, P. Gahan, "Comparison between J48 Decision Tree, SVM and MLP in Weather Forecasting" SSRG International Journal of Computer Science and Engineering 3.11 (2016): 39-44.

APA Style:

Suvendra Kumar Jayasingh, Jibendu Kumar Mantri, P. Gahan,(2016). Comparison between J48 Decision Tree, SVM and MLP in Weather Forecasting. SSRG International Journal of Computer Science and Engineering 3(11), 39-44.

Abstract:

 Weather forecasting is a challenging task for the Government and the general public throughout the world. Literature survey shows that the soft computing techniques play better role in predicting the weather at a particular region than the traditional mathematical or statistical methods. Nowa- days the data mining and soft computing techniques have attained the most position in research for predicting accurate weather. This paper depicts a comparison between the 3 different soft computing techniques like J48 Decision Tree, Support Vector machine and Multi Layer Perceptions (MLP) in weather forecasting. Time series data of Delhi is collected for 5 years and fed to the 3 models. After training to the 3 models, results were compared and it was concluded that the performance of J48 decision tree is consistently better.

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Key Words:

J48 Decision Tree, Support Vector Machine, Multi Layer Perceptron, Time Series Data, Weather Forecasting, WEKA (Waikato Experient and knowledge Analysis).