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|
How to Cite?
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 , vol. 3, no. 11, pp. 39-44, 2016. Crossref, https://doi.org/10.14445/23488387/IJCSE-V3I11P109
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.
J48 Decision Tree, Support Vector Machine, Multi Layer Perceptron, Time Series Data, Weather Forecasting, WEKA (Waikato Experient and knowledge Analysis).
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