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Multiple Linear Regressions for Predicting Rainfall for Bangladesh
Volume 6, Issue 1, March 2018, Pages: 1-4
Received: Nov. 22, 2017; Accepted: Dec. 5, 2017; Published: Feb. 6, 2018
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MAI Navid, Department of Science, Ruhea College Rangpur, Bangladesh
NH Niloy, Department of Science, Ruhea College Rangpur, Bangladesh
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Agricultural economy is largely based upon crop productivity and rainfall. For analyzing the crop productivity, rainfall prediction is require and necessary to all farmers. Rainfall Prediction is the application of science and technology to predict 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. Data mining might be used to make precise predictions for rainfalls. Most widely used techniques for rainfall is clustering, artificial neural networks, linear regression etc. In this article multiple linear regressions used for predicting rainfall in Bangladesh.
Multiple Linear Regression, Data Mining, Rainfall Prediction
To cite this article
MAI Navid, NH Niloy, Multiple Linear Regressions for Predicting Rainfall for Bangladesh, Communications. Vol. 6, No. 1, 2018, pp. 1-4. doi: 10.11648/
Copyright © 2018 Authors retain the copyright of this article.
This article 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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