Electrical energy demand forecasting model using artificial neural network: A case study of Lagos State Nigeria

Article history: Received: January 01, 2019 Received in revised format: March 6, 2019 Accepted: May 24, 2019 Available online: May 24, 2019 Electrical Energy is an essential commodity which significantly contributes to the economic development of any country. Many non-linear factors contribute to the final output of electrical energy demand. In order to efficiently predict electrical energy demand, many time-series analysis and multivariate techniques have been suggested. In order for these methods to accurately work, an enormous quantity of historical dataset is essential which sometimes are not available, inadequate and inaccurate. To overcome some of these challenges, this paper presents an Artificial Neural Network based method for Electrical Energy Demand Forecasting using a case study of Lagos state, Nigeria. The predicted values are compared with actual values to estimate the performance of the proposed technique. © 2019 by the authors; licensee Growing Science, Canada.

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