Abstract
This paper presents a Grey-Markov forecasting model for forecasting the electric power requirement in China. This method takes into account the general trend series and random fluctuations about this trend. It has the merits of both simplicity of application and high forecasting precision. This paper is based on historical data of the electric power requirement in China, and forecasts and analyzes the electric power requirement in China by the Grey–Markov forecasting model. The forecasting precisions of Grey-Markov forecasting model from 2002 to 2004 are 99.42%, 98.05% and 97.56%, and those of GM(1,1) grey forecasting model are 98.53%, 94.02% and 88.48%. It shows that the Grey-Markov forecasting models have higher precision than GM(1,1) grey forecasting model. The results provides scientific basis for the planned development of the electric power supply in China.
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© 2005 Springer-Verlag Berlin Heidelberg
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He, Y., Huang, M. (2005). A Grey-Markov Forecasting Model for the Electric Power Requirement in China. In: Gelbukh, A., de Albornoz, Á., Terashima-Marín, H. (eds) MICAI 2005: Advances in Artificial Intelligence. MICAI 2005. Lecture Notes in Computer Science(), vol 3789. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11579427_58
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DOI: https://doi.org/10.1007/11579427_58
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29896-0
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