期刊名称：International Journal of Data and Network Science
印刷版ISSN：2561-8148
电子版ISSN：2561-8156
出版年度：2019
卷号：3
期号：4
页码：305-322
DOI：10.5267/j.ijdns.2019.5.002
出版社：Growing Science
摘要：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.
关键词：Artificial Neural Network; Electrical Energy Demand Forecasting; Recurrent Neural Network
