The engineering of knowledge-based systems: theory and practice
The engineering of knowledge-based systems: theory and practice
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Using genetic algorithm to develop a neural-network-based load forecasting
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
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In this work, an Artificial Neural Network (ANN) is combined to Heuristic Rules producing a powerful hybrid intelligent system for short and mid-term electric load forecasting. The Heuristic Rules are used to adjust the ANN output to improve the system performance. The study was based on load demand data of Energy Company of Pernambuco (CELPE), which contain the hourly load consumption in the period from January-2000 until December-2004. The more critical period of the rationing in Brazil was eliminated from the data file, as well as the consumption of the holidays. For this reason, the proposed system forecasts a holiday as one Saturday or Sunday based on the specialist's information. The result obtained with the proposed system is compared with the currently system used by CELPE to test its effectiveness. In addition, it was also compared to the result of the ANN acting alone.