An improved combination forecasting method based on IOWA operator and application
Longhua Mu · Power System Protection and Control · 2011
The combination forecasting model based on induced ordered weighted averaging(IOWA) operators,which is built according to the criterion of error sum of squares,failes to reflect the influence of errors arising from observation points in various periods on the predictive values.Moreover,this method can not be used to predict directly because future data are unknown in actual forecasting.In order to overcome the above flaws,an improved method is proposed.First,individual forecasting model that has higher forecasting accuracy is chosen as a criterion.Then,the deviation of predictive values between other models and standard model is computed.The weights are given according to the mean value size of the absolute value sum of deviation in every individual forecasting model in every period.Finally,a new forecasting model is built in accordance with the weighted error sum of squares.And genetic algorithm is used to solve the optimal weights.Verified by an example,the improved combination forecasting method is better than the original combination forecasting method based on IOWA operator.Forecasting accuracy is improved effectively.