preprocessing technique, prediction model, and post processing technique. In this thesis, Kalman filter method has been used for pre-processing of input raw data. Although pre-processed methods of data are generally anticipated to increase the accuracy of forecasts with different methods such as reduction of dimensions, removal of Perth data, reduction of incomplete data, noise elimination, etc., some data may be removed as noise in the filtering process, which will reduce the accuracy of the anticipated performance
