@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},
	}