A Multiple Linear Regression Model To Predict Rainfall Using Indian Meteorological Data

  • N. Gnanasankaran, E. Ramaraj

Abstract

In the present times, precise forecasting of rainfall (precipitation) is not easy owing to the complexity of meteorological phenomena. Weather forecasting is essential for several catchment management applications, especially for flood warning systems. The problem of weather forecasting can be considered as a regression problem, which can be solved by machine learning (ML) algorithms. ML technique is a procedure of learning particular tasks with no human interference and enhancing the results through the continuous learning process. This paper presents a new multiple linear regression (MLR) model for precise rainfall forecasting. The MLR model is tested using a set of meteorological data including the monthly wise rainfall details in India. The proposed model shows better rainfall prediction performance over the compared methods under several performance measures. The results obtained clearly ensured that the MLR model has offered supreme outcome over the compared methods.

Published
2020-04-21
How to Cite
N. Gnanasankaran, E. Ramaraj. (2020). A Multiple Linear Regression Model To Predict Rainfall Using Indian Meteorological Data. International Journal of Advanced Science and Technology, 29(8s), 746 - 758. Retrieved from http://sersc.org/journals/index.php/IJAST/article/view/10816