The prediction of energy consumption plays an important role in energy management system of enterprise. This paper presents an algorithm of grey model-GM(1,1) to forecast the energy consumption of enterprise. In this article, the principle of grey prediction is analyzed and grey model- GM(1,1) is established, at the same time, the validation of method is verified by making use of the sampled data of compressed air consumption from steel workshop. The average relative error of grey model-GM(1,1) is no more than 1%. The result shows that grey model-GM(1,1) has higher prediction precision and the trend of energy consumption can be reflected accurately in actual energy consumption forecasting. © 2012 Springer-Verlag.
CITATION STYLE
Yu, X., & Lu, Z. (2012). Prediction of energy consumption based on grey model - GM (1,1). In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7530 LNAI, pp. 192–199). https://doi.org/10.1007/978-3-642-33478-8_25
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