A Comparative Study of Machine Learning Algorithms for Weather Prediction in India

Weather prediction is crucial in India due to its diverse geographical and climatic conditions. Over the recent years, machine learning has demonstrated remarkable advancements in enhancing the reliability and accuracy of weather forecasting. However, India's geographical and climatic diversity necessitates the identification of algorithms capable of providing accurate forecasts across various regions and seasons. To address this, a comprehensive comparative study was conducted, delving into the effectiveness of different machine learning algorithms for weather prediction across India. This study examines how these algorithms perform across the intricate landscape of the country, considering factors like temperature, humidity, air pressure and precipitation. By evaluating their performance under different conditions, this research aims to identify the most suitable algorithms for accurate and reliable weather forecasting across India, making it easier for researchers to analyze data source sensitivity and algorithm suitability for different types of weather parameters and the associated datasets.