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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM1804

Rainfall Prediction Using Machine Learning Techniques

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM1804

Volume:

3 |

8 |

Aug 2019

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

AM

Abhishek ML

HV

Harshavardhan V

SB

Sudesh Bhat

SJ

Sujay J

VKMMKB

Vinay K M MAHENDRA KUMAR B

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Abstract

India is an agricultural country and its 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. Using different data mining techniques it can predict rainfall. Data mining techniques are used to estimate the rainfall numerically. This paper focuses some of the popular data mining algorithms for rainfall prediction. Random Forest, K-Nearest Neighbor algorithm, Logistic regression, Decision Tree are some of the algorithms have been used. From that comparison, it can analyze which method gives better accuracy for rainfall prediction.

KEYWORDS

Rain fall Agricultural Economy Farmers Water resources.

Cite This Article

Abhishek ML, Harshavardhan V, Sudesh Bhat, Sujay J, Vinay K M MAHENDRA KUMAR B, "Rainfall Prediction Using Machine Learning Techniques," International Journal of Scientific Research in Engineering and Management, vol. 3, no. 8, Aug 2019.

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Publication Date

4/27/2024

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Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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