期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2013
卷号：3
期号：4
出版社：S.S. Mishra
摘要：Short Term Load Forecasting(STLF) varies from an hour to hour and is used for requirem ent for control, unit commitment, security assessment, optimum planning of power generation, and pla nning of both spinning reserve and energy exchange, also as inputs to load flow studies and contingency analysis. Artificial neural networks (ANN's) has drawbacks like inputs nodes or hidden nodes which can cause training file difficulties, more computation time, large size data, less flexibility etc. Generalized neuron model (GNM) have more flexibility, no hidden layers, less computation time, usage of .and .neurons etc. In this paper, development of STLF using GNM under different error gradients functions is obtained.
关键词：Artificial neural networks; Error gradient functions; Generalized Neuron model; Short term load ;forecasting.
