Energy consumption forecasting using a bi-objective fuzzy linear regression model

Masoud Rabbani, S.M. Ghoreyshi, H. Rafiei and M. Ghazanfari

International Journal of Services and Operations Management, 2012, vol. 13, issue 1, 1-18

Abstract: In this paper, a new bi-objective fuzzy linear regression model is proposed in order to fill the gap in the field of forecasting using possibilistic programming. Additionally, the proposed model is compared with three promising fuzzy linear regression models from literature in order to forecast the energy consumption in USA, Japan, Canada, and Australia during 2010 to 2015. In the fuzzy regression models, independent variables are population, cost of crude oil, gross domestic production (per capita), and annual energy production where dependent variable is energy consumption. In order to train the models and estimate their parameters, historical data from 1990 to 2005 are used for each country. Then, the models performance in energy consumption forecasting is tested using actual data from 2006 to 2009. Based on results of mean absolute percentage error (MAPE), the proposed model outperforms other models. Finally, the energy consumption in USA, Japan, Canada, and Australia is forecasted for 2010 to 2015 using the proposed model. The results show that the proposed model provides accurate solution for energy consumption problem.

Keywords: fuzzy linear regression; FLR; energy consumption; forecasting; bi-objective modelling; USA; United States; Japan; Canada; Australia; population; crude oil prices; gross domestic production; GDP; annual energy production. (search for similar items in EconPapers)
Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijsoma:v:13:y:2012:i:1:p:1-18

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