Electric power utilities require forecast of system some drawbacks such as inaccurate prediction, difficulty in demand or electrical load for one to seven days ahead. This modeling processes, numerical instability, requirement of paper studies a short-term electric load forecasting technique large historical database, and demand of high human using a multi-layered feedforward Artificial Neural Network (ANN) and a fuzzy set-based classification algorithm. The Recently. the application of the artificial neural network hourly data is subdivided into various class of weather (ANN) to short-term load forecasting has gained a great deal conditions using the fuzzy set representation of weather of interest and several researchers have reported the variables and then the ANN'S are trained and used to perform effectiveness of the ANN approach [ 6, 7, 8 1. Unlike the the load forecasting up to 120 hours ahead with a remarkable previous techniques, the ANN leams the patterns from the accuracy. inputs and outputs of the utilities' system and then, it creates expertise.

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