Rain Fall Prediction using Data Mining Techniques with Modernistic Schemes and Well-Formed Ideas
Deepak Sharma1, Priti Sharma2
1Deepak Sharma*, Research Scholar, Department of Computer Science and Applications, MD University, Rohtak, India.
2Dr. Priti Sharma, Assistant Professor, Department of Computer Science and Applications, MD University, Rohtak, India. Email:
Manuscript received on October 15, 2019. | Revised Manuscript received on 24 October, 2019. | Manuscript published on November 10, 2019. | PP: 258-263 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4011119119/2019©BEIESP | DOI: 10.35940/ijitee.A4011.119119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Weather forecasting is essential because it helps to deal with the environment related future anomalies. Accurate and timely predications can contribute largely for taking safety measures in the ongoing projects such as agriculture tasks, flight operations, transportation tasks and many others. There are large number of meteorologist all over the world who are trying their level best to predict the aspects of environment using data mining techniques. This paper contains some of the best work done in rain fall prediction using data mining techniques. This paper helps the researchers to study the literature of this field in a crisp, summarized and encapsulated way.
Keywords: Data Mining, Bayesian Classifier, Clustering, Rain Fall Prediction, Linear Regression Technique, K-fold, Weather Predictions, Multiple Regression Technique.
Scope of the Article: Clustering