@article{(Open Science Index):https://publications.waset.org/pdf/554, title = {Artificial Neural Network Approach for Short Term Load Forecasting for Illam Region }, author = {Mohsen Hayati and Yazdan Shirvany}, country = {}, institution = {}, abstract = {In this paper, the application of neural networks to study the design of short-term load forecasting (STLF) Systems for Illam state located in west of Iran was explored. One important architecture of neural networks named Multi-Layer Perceptron (MLP) to model STLF systems was used. Our study based on MLP was trained and tested using three years (2004-2006) data. The results show that MLP network has the minimum forecasting error and can be considered as a good method to model the STLF systems. }, journal = {International Journal of Electrical and Computer Engineering}, volume = {1}, number = {4}, year = {2007}, pages = {667 - 671}, ee = {https://publications.waset.org/pdf/554}, url = {https://publications.waset.org/vol/4}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 4, 2007}, }