首页    期刊浏览 2024年12月03日 星期二
登录注册

文章基本信息

  • 标题:A Multi-Level Fuzzy Linear Regression Model for Forecasting Industry Energy Demand of Iran
  • 本地全文:下载
  • 作者:Aliyeh Kazemi ; Aliyeh Kazemi ; Amir Foroughi. A
  • 期刊名称:Procedia - Social and Behavioral Sciences
  • 印刷版ISSN:1877-0428
  • 出版年度:2012
  • 卷号:41
  • 页码:342-348
  • DOI:10.1016/j.sbspro.2012.04.039
  • 语种:English
  • 出版社:Elsevier
  • 摘要:AbstractThe aim of this paper is to develop a prediction model of energy demand of industry sector in Iran. A fuzzy-based approach is applied for the industry energy demand forecasting using socio-economic indicators. This approach is structured as a fuzzy linear regression (FLR). A multi-level FLR model is designed properly. This paper indeed proposes a multi-level FLR model by which the inputs to the ending level are obtained as outputs of the starting levels. Actual data from 1994-2008 are used to develop the multi-level FLR and illustrate capability of the approach in this regard. The estimation fuzzy problem for the model is formulated as a linear optimization problem and is solved using the linear programming based simplex method. Furthermore, having obtained the fuzzy parameters, the industry energy demand is predicted from 2011 to 2020. The results provide scientific basis for the planned development of the energy supply of industry sector in Iran.
  • 关键词:Energy consumption;Industry sector;Forecasting;FLR
国家哲学社会科学文献中心版权所有