@article{article_345731, title={Medium-Term Load Forecasting by Artificial Neural Network based Differential Evolution}, journal={International Journal of Engineering Research and Development}, volume={3}, pages={28–32}, year={2011}, author={Eke, İbrahim}, keywords={Load forecasting,differential evolution,artificial neural network}, abstract={<p align="justify">Load forecasting is an important part of the power generation process. For years, it has been achieved by traditional approaches stochastic like time series; but, new methods based on artificial intelligence emerged recently in literature and started to replace the old ones in the industry. This study presents an intelligent hybrid approach called DE-ANN by hybridization of Differential Evolution (DE) and Artificial Neural Network. In this work, performance of the Differential Evolution, a recently proposed algorithm, has been tested on training on Artificial Neural Networks. The performance of the algorithm has been compared to traditional Artificial Neural Networks Results show that DE algorithm outperforms the other method. <br> </p>}, number={1}, publisher={Kirikkale University}