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Paper Title
Rainfall Prediction using Machine Learning
Authors
Vishal Pandey, Abhishek Singh, Santosh Singh
Keywords
Rainfall Prediction, Machine Learning Model, Regression Analysis, Random Forest, Data Preprocessing, Accuracy Assessment
Abstract
Agrarian nations like India are highly dependent on rainfall amounts to determine the success or failure of agriculture. Most of India's agricultural produce relies on the monsoon rains and its precipitation patterns. Monsoon season provides for most water needs in India. For adequate crop planning, it is important to know average rainfall. Several experiments say that precipitation directly affects crops. Therefore, this study used machine learning techniques and algorithms to analyse Indian states' rainfall patterns using rainfall data from government during 1901-2017 period. The study concludes that machine learning algorithms are useful in analyzing and investigating about Indian states' rain fall with comparable results to those in industry standards.
IJCRT's Publication Details
Unique Identification Number - IJCRT2403698
Paper ID - 253611
Page Number(s) - f843-f848
Pubished in - Volume 12 | Issue 3 | March 2024
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Vishal Pandey, Abhishek Singh, Santosh Singh, "Rainfall Prediction using Machine Learning", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 3, pp.f843-f848, March 2024, Available at :http://www.ijcrt.org/papers/IJCRT2403698.pdf
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Volume 13 | Issue 11
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Last Date :
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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