Somalia Weather Forecast Using Machine Learning

Abstract

Generally, weather affects us in different ways. Sometimes, too much hot weather for a long time without any rain can cause drought, also huge storms with strong winds, such as tornadoes can do a great number of damages to the buildings, farms, etc. However, hot weather prevails all year in east Africa particularly Somalia. In Somalia there are different sports that take place every year. Weather conditions have a significant impact on outdoor sports such as track and field, football, and tennis. Those outdoor games occur in some cities and some in regions. For outdoor sports, weather conditions are an important aspect to consider while designing a game. Machine learning represents a far bigger possibility in the growth of weather forecasting, so I try five (SVR, DT, RF, GB, MLP) models to test that. Those models/algorithms can predict the weather of three cities of Somalia such as Mogadishu, Kismayo, and Hargeisa. The model's reliability forecast was calculated between real and forecasted values by calculating the MAE, MSE and its accuracies. The results suggest that the Random Forest model might be beneficial for Somalia weather to forecast