Rainfall prediction using Machine Learning Techniques
G. Bala Sai Tarun1, J.V. Sriram2, K. Sairam3, K. Teja Sreenivas4, M.V.B.T. Santhi5
1G. Bala Sai Tarun, Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur, India.
2J.V. Sriram, Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur, India.
3K. Sairam, Department of CSE, Koneru Lakshmaiah Education Foundation, Guntur, India.
4K. Teja Sreenivas, Koneru Lakshmaiah Education Foundation, Guntur, India.
5M V B T Santhi, Associate Professor, Department of Computer Science Engineering, KLEF Guntur, India.
Manuscript received on 05 May 2019 | Revised Manuscript received on 12 May 2019 | Manuscript published on 30 May 2019 | PP: 957-963 | Volume-8 Issue-7, May 2019 | Retrieval Number: G5295058719/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: Rainfall prediction is very important in several aspects of our economy and can help us preventing serious natural disasters. Some areas in India are economically dependent on rainfall as agriculture is primary occupation of many states. This helps to identify crops patterns and correct management of water resources for the crops. For this, linear and non-linear models are commonly used for seasonal rainfall prediction. Few algorithms used for rainfall prediction are CART, Genetic Algorithms and SVM, these are computer aided rule-based algorithms. In this paper, we performed qualitative analysis using few classification algorithms like Support vector machines (SVM), Artificial Neural Networks, Logistic regression. Dataset used for this classification application is taken from hydrological department of Rajasthan. Overall, we analyze that algorithm which is feasible to be used in order to qualitatively predict rainfall.
Keyword: Rainfall Prediction, Correlation based feature selection, Machine Learning
Scope of the Article: Machine Learning