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Journal: International Journal of Computer Science and Mobile Applications IJCSMA (Vol.2, No. 2)

Publication Date:

Authors : ;

Page : 84-88

Keywords : Naive Bayes; K- Nearest Neighbour algorithm; Decision Tree; Neural Network; Fuzzy Logic;

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India is an agricultural country and its economy is largely based upon crop productivity. For analyzing the crop productivity, rainfall prediction is require and necessary. Rainfall Prediction is the application of science and technology to foretell the state of the atmosphere. It is important to exactly determine the rainfall for effective use of water resources, crop productivity and pre planning of water structures. Using data mining techniques we can predict rainfall. Data mining techniques are used to estimate the rainfall numerically. This paper focuses some of the data mining algorithms for rainfall prediction. Naive Bayes, K- Nearest Neighbour algorithm, Decision Tree, Neural Network and fuzzy logic are some of the algorithms compared in this paper. From that comparison, we can analyze which method gives better accuracy for rainfall prediction.

Last modified: 2014-02-23 03:15:42