Predicting primary energy consumption using NDGM(1,1,k,c) model with Simpson formula

Document Type : Article

Authors

1 - School of Science, Southwest University of Science and Technology, 621010, Mianyang, China. - V.C. and V.R. Key Lab of Sichuan Province, Sichuan Normal University, 610068, Chengdu, China

2 - School of Science, Southwest University of Science and Technology, 621010, Mianyang, China. - State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, 610500, Chengdu, China.

3 - School of Science, Southwest Petroleum University, 610500, Chengdu, China - State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation, Southwest Petroleum University, 610500, Chengdu, China

4 College of Engineering and Technology, Southwest University, 400715, Chongqing, China

5 College of Business Planning, Chongqing Technology and Business University, 400067, Chongqing, China

Abstract

Energy consumption plays a key role in economics development for all countries. Catching the future trend of energy consumption is very important for the governments and energy companies. In this paper, the primary energy consumption of Saudi Arabia, India, Philippines and Vietnam are systematically studied by various forecasting models. Based on the actual data from 2006 to 2016, a novel grey forecasting model termed NDGM_S (1,1,k,c) is proposed where the Simpson numerical integration formula is applied to construct the background value. The time response function and the restored value of the present model are deduced, and then the unbiased property is proved. As shown in the computational results, the NDGM_S (1,1,k,c) model can achieve better prediction accuracy than other forecasting models, and it is quite suitable for predicting sequence with homogeneous/non-homogeneous exponential law.

Keywords

References

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Scientia Iranica
Volume 28, Issue 6 - Serial Number 6
Transactions on Computer Science & Engineering and Electrical Engineering (D)
November and December 2021
Pages 3379-3395

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History

  • Receive Date: 09 June 2018
  • Revise Date: 02 February 2019
  • Accept Date: 18 November 2019

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