期刊名称：International Journal of Research in Management, Science & Technology
印刷版ISSN：2321-3264
出版年度：2013
卷号：1
期号：2
出版社：Prannath Parnami Institute of Management & Technology, Hisar
摘要：Mid-term forecasting of load demand is necessary for the correct operation of electric utilities. There is an on-going attention toward putting new approaches to the task. Recently, Neurofuzzy modeling has played a successful role in various applications over nonlinear time series prediction. This paper presents a neurofuzzy model for long-term load forecasting. This model is identified through Locally Linear Model Tree(LoLiMoT) learning algorithm. The model is compared to a multilayer perceptron and hierarchical hybrid neural model (HHNM). The models are trained and assessed on load data extracted from state load dispatch center, Tutu, Shimla, India
关键词：MTLF; ANN; Load Forecasting; MAPE and Max APE.
