Fadare, D. A.Dahunsi, O. A.2018-10-112018-10-112009-111551-7624ui_art_fadare_modeling_2009The Pacific Journal of Science and Technology 10(2), pp. 471-478http://ir.library.ui.edu.ng/handle/123456789/2053In this study, the short-term load pattern for the University of Ibadan was investigated and a multi-layered feed-forward artificial neural networks (ANN) model was developed to forecast the time series half-hourly load pattern of the system using the load data for a period of 5 years (2000 to 2004). The study showed that the mean half-hourly load for the period of study ranged between 1.3 and 2.2 MW, and the coefficient of determination (R2-values) of the ANN predicted and the measured half-hourly load for test dataset decreased from 0.6832 to 0.4835 with increase in the lead time from 0.5 to 10.0 hours.enArticle