Machine Learning based Rainfall Prediction

Vivek Rajendra Dhokane, Arunadevi Khaple, Rashmi Ashtagi

Zenodo (CERN European Organization for Nuclear Research) · 30 March 2022

In one sentence. Multiple linear regression predicts rainfall from Indian weather parameters and claims to beat textbook algorithms, but gives no quantitative results.

Abstract

Weather forecast is one of the most important ways to predict the weather in any country. This paper proposes a rain forecast model using Multiple Linear Regression (MLR) on the Indian database. Input data has more weather parameters and rainfall prediction more accurately. Mean Square Error (MSE), precision, correlation parameters are used to validate the proposed model. From the results, the proposed machine learning model provides much better results than other algorithms in the textbooks. There are many hardware tools to predict rainfall through climatic conditions such as temperature, humidity, pressure. These traditional methods cannot work in them an effective way so that by using machine learning techniques we can produce accurate results. We can just do it has a history of rain data analysis and can predict future rainfall. Different strategies produce different accuracy is therefore important to choose the right algorithm and model according to requirements.

Labels

Labels and summary are generated by Claude and reviewed weekly. Wrong? Edit this entry.