To Predict Rain Fall in Desert Area of Rajasthan Using Data Mining Techniques
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 5
Abstract
Weather forecasting has always been one of the most challenging problems in the desert areas of Rajasthan. Rainfall has become a significant and technical factor in the desert state of India like Rajasthan. Data mining is the process that attempts to discover patterns in large data sets. It utilizes methods at the intersection of artificial intelligence, machine learning, statistics, and systems. There are various forecasting methods available for the prediction of rainfall and among these methods data mining techniques can be effectively used in predicting rainfall, humidity and wind pressure. Some of the techniques are called as Empirical techniques and others are called as called dynamic techniques. In the empirical method, historical data of the rainfall is compared and processed with the available climatic variables of different parts of the globally available data. Regression, Artificial Neural Network, fuzzy logic etc. are the most widely used techniques under empirical approaches. Whereas, in dynamic approach predictions are created by physical model and is implemented using numerical rainfall forecasting method. Clustering, classification and Multiple Linear Regression are used in this paper for rainfall prediction.
Authors and Affiliations
Peeyush Vyas
Keywords
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