Analysis and Prediction of Weather Condition in Ethiopia

Weather prediction involves a combination of computer models, observations and knowledge of trends and patterns, by using of which reasonably accurate forecasts can be made up to a finite number of days in advance. This study is aimed at investigating and modelling the existing weather data series to enable the future information of the weather condition to be forecasted accurately, using machine learning approach. The book presents a research on weather forecasting by using historical weather datasets. Since atmospheric pattern is a complex and non-linear system, traditional methods are seized to be effective and efficient in such situations. It is observed that Artificial Neural Networks, including MLP, GRNN, RBF and Elman recurrent networks are influential methods for solving such problems.The criteria used for model selection include MSE, MAE, RMSE, correlation coefficient and confusion matrix.