Electricity Consumption Prediction Based on SVR with Ant Colony Optimization - Haijiang Wang; Shanlin Yang (Indonesian Journal of Electrical Engineering and Computer Science, 2013)
Accurate forecasting of electric load has always been the most important issues in the electricity industry, particularly for developing countries. Due to the various influences, electric load forecasting reveals highly nonlinear characteristics. This paper creates a system for power load forecasting using support vector machine and ant colony optimization. The method of colony optimization is employed to process large amount of data and eliminate. The SVR model with ant colony optimization is proposed according to the characteristics of the nonlinear electricity consumption data. Then ACO-SVR model is applied to the electricity consumption prediction of Jiangsu province. The result shows better than the ANNs method and improves the accuracy of the prediction. DOI: http://dx.doi.org/10.11591/telkomnika.v11i11.3557