標題: Forecasting energy consumption using a grey model improved by incorporating genetic programming
作者: Lee, Yi-Shian
Tong, Lee-Ing
工業工程與管理學系
Department of Industrial Engineering and Management
關鍵字: Energy consumption;Grey forecasting model;Genetic programming
公開日期: 1-Jan-2011
摘要: Energy consumption is an important economic index, which reflects the industrial development of a city or a country. Forecasting energy consumption by conventional statistical methods usually requires the making of assumptions such as the normal distribution of energy consumption data or on a large sample size. However, the data collected on energy consumption are often very few or non-normal. Since a grey forecasting model, based on grey theory, can be constructed for at least four data points or ambiguity data, it can be adopted to forecast energy consumption. In some cases, however, a grey forecasting model may yield large forecasting errors. To minimize such errors, this study develops an improved grey forecasting model, which combines residual modification with genetic programming sign estimation. Finally, a real case of Chinese energy consumption is considered to demonstrate the effectiveness of the proposed forecasting model. (C) 2010 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/j.enconman.2010.06.053
http://hdl.handle.net/11536/26143
ISSN: 0196-8904
DOI: 10.1016/j.enconman.2010.06.053
期刊: ENERGY CONVERSION AND MANAGEMENT
Volume: 52
Issue: 1
起始頁: 147
結束頁: 152
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