Analysis of various climate change parameters in India using machine learning

TL;DR

This paper employs machine learning techniques to analyze and predict 17 climate change parameters in India, aiming to aid in proactive planning and awareness to combat adverse climate impacts.

Contribution

It introduces a predictive model using regression methods for 17 climate parameters specific to India, providing future estimates to support climate action.

Findings

Model predicts climate parameters for 2025, 2030, 2035

Provides accurate estimates for all 17 parameters

Aims to enhance climate preparedness in India

Abstract

Climate change in India is one of the most alarming problems faced by our community. Due to adverse and sudden changes in climate in past few years, mankind is at threat. Various impacts of climate change include extreme heat, changing rainfall patterns, droughts, groundwater, glacier melt, sea-level rise, and many more. Machine Learning can be used to analyze and predict the graph of change using previous data and thus design a model which in the future can furthermore be used to catalyze impactful work of climate change and take steps in the direction to help India fight against the upcoming climate changes. In this paper, we have analyzed 17 climate change parameters about India. We have applied linear regression, exponential regression, and polynomial regression to the parameters and evaluated the results. Using the designed model, we will predict these parameters for the years 2025,2030, 2035. These predicted values will thus help our community to prevent and take actions against the adverse and hazardous effects on mankind. We have designed and created this model which provides accurate results regarding all 17 parameters. The predicted values will therefore help India to be well equipped against climate change. This data when made available to the people of India will help create awareness among them and will help us save our country from the haphazard effects of climate change.