MASTER’S THESIS AT BASRA UNIVERSITY DISCUSSES MODELING AND PREDICTION OF ELECTRICAL LOAD FLUCTUATIONS USING SUPPORT VECTOR REGRESSION WITH CHAOTIC ALGORITHMS IN THE SOUTHERN REGION

MASTER’S THESIS AT BASRA UNIVERSITY DISCUSSES MODELING AND PREDICTION OF ELECTRICAL LOAD FLUCTUATIONS USING SUPPORT VECTOR REGRESSION WITH CHAOTIC ALGORITHMS IN THE SOUTHERN REGION:

On Monday 10/1/2022, the College of Administration and Economics at the University of Basra discussed a master’s thesis in the Department of Statistics on modeling and forecasting electrical load fluctuations using support vector regression with chaotic algorithms in the southern region.

The thesis of the researcher (Huda Abdel-Sada Hashem) aims to create hybrid statistical models from the regression of the support vector with chaotic algorithms, then compare these models to choose the best one according to statistical criteria and use the chosen model in predicting the consumption of electric energy in the southern region.

The thesis concluded that the combination of the support vector regression model and the chaotic algorithms improve the prediction accuracy. This model gave good, efficient predictions that are close to the actual values ​​of the annual electric energy consumption series.