• Corpus ID: 6390557

Artificial Neural Network Approach for Short Term Load Forecasting for Illam Region

@article{Hayati2007ArtificialNN,
  title={Artificial Neural Network Approach for Short Term Load Forecasting for Illam Region},
  author={Mohsen Hayati and Yazdan Shirvany},
  journal={International Journal of Electrical and Computer Engineering},
  year={2007},
  volume={1},
  pages={667-671}
}
  • M. Hayati, Y. Shirvany
  • Published 24 April 2007
  • Computer Science
  • International Journal of Electrical and Computer Engineering
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… 

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