Predicting Precipitation Using K-Nearest Neighbor Algorithm for Jalgaon, Dhule and Nandurbar Districts

  • Husain H. Dawoodi, Manoj P. Patil

Abstract

Rainfall is one of the major elements and has a crucial role in the agricultural sector, especially in the North Maharashtra region where the economy is mainly dependent on the agricultural yields. Currently, the precipitation prediction for the North Maharashtra region is not accurate, resulting in socio-economic loss to farmers. In recent years artificial intelligence is widely used for forecasting and prediction of precipitation. In this paper K-nearest neighbor (KNN) algorithm is used to predict precipitation in three districts of the North Maharashtra Region namely: Jalgaon, Dhule and Nandurbar from the metrological data of 2009- 2018. The extensive experimental results demonstrate that KNN predicts precipitation with 96% accuracy. This study reveals that KNN has the potential to predict precipitation in the North Maharashtra region with better accuracy in the prediction of precipitation.

Published
2020-06-01
How to Cite
Husain H. Dawoodi, Manoj P. Patil. (2020). Predicting Precipitation Using K-Nearest Neighbor Algorithm for Jalgaon, Dhule and Nandurbar Districts. International Journal of Advanced Science and Technology, 29(8s), 5259 - 5264. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/27418