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Rainfall prediction using machine learning techniques.

Authors :
Shabu, S. L. Jany
Refonaa, J.
Devi, D.
Aishwarya, D.
Babu, K. Krishna
Reddy, K. Purshotham
Source :
AIP Conference Proceedings. 2024, Vol. 2850 Issue 1, p1-6. 6p.
Publication Year :
2024

Abstract

India is a farming nation and its economy is to a great extent dependent on rainforest creation. Downpour estimates are vital and fundamental for all ranchers to examine crop yields. Unsurprising rainfall is the capacity to foresee the climate with the assistance of science and innovation. It is essential to know how much rainfall to utilize water assets, horticultural creation and water arranging proficiently. Various strategies for information mining can foresee rainfall. Information extraction is utilized to appraise rainfall. This article features probably the most well-known rainfall forecast calculations. Guileless Bayes, K-Near Neighbour Algorithm, and Certificate Tree are a portion of the calculations contrasted with this record. According to a relative perspective, it is feasible to break down how rainfall is accurately anticipated. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094243X
Volume :
2850
Issue :
1
Database :
Academic Search Index
Journal :
AIP Conference Proceedings
Publication Type :
Conference
Accession number :
177323168
Full Text :
https://doi.org/10.1063/5.0208435