A Systematic Review on Weather Forecasting using Machine Learning Techniques

Numerical Weather Prediction (NWP) is a typical method for weather forecasting. Though sometimes it might result in unsatisfactory performance because to incorrect initial state setting. A data-driven strategy learns from historical data while integrating prior knowledge from NWP, augmented by an efficient information fusion mechanism. To predict something, a background study is required to understand the pattern. On Earth, every aspect of human life is impacted by nature. Because we cannot avoid the natural changes and conditions, we have chosen to reduce their effect on our lives. Hence, to achieve this, it is essential to have prior knowledge of the weather conditions to make things work in accordance with the changes in the environment. To perform prediction, an accurate classification of data is required. The development of a weather prediction model is the main goal of this paper. Agriculture is the field that is most influenced by the weather. Therefore, it can expand the scope to provide regional guidelines to farmers based on the conducted classification.