Real-time Weather Estimation and Forecasting Using Hybrid Machine Learning Approaches

In real-time forecasting, estimation is the most crucial measurement for atmospheric observations by time and area. Present-day weather conditions observations are most important for many things, like agriculture, and different types of calamities that are unexpected in normal life. Machine learning techniques are used for weather forecasting. Among machine learning regression techniques, a key role is played in this problem. It monitors continuously from time to time. Temperature predictions also include weather forecasting by using regression techniques. Multiple regression techniques were used in our research. We measure the MSE rate for every technique. Multiple variety of metrics were tested. We consider short MSE to indicate for best forecasting outcome.