4.7 Article

A novel Grey Bernoulli model for short-term natural gas consumption forecasting

Journal

APPLIED MATHEMATICAL MODELLING
Volume 84, Issue -, Pages 393-404

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.apm.2020.04.006

Keywords

Forecasting; Grey bernoulli model; Particle Swarm Optimization; Natural gas consumption

Funding

  1. National Natural Science Foundation of China [71901184, 71771033, 71571157, 11601357]
  2. Humanities and Social Science Project of Ministry of Education of China [19YJCZH119]
  3. National Statistical Scientific Research Project [2018LY42]
  4. Applied Basic Research Program of Science and Technology Commission Foundation of Sichuan province [2017JY0159]
  5. V.C. & V.R. Key Lab of Sichuan Province [SCVCVR2018.08VS, SCVCVR2019.05VS]
  6. State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation (Southwest Petroleum University) [PLN 201710]

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This paper investigates the natural gas consumption of the United States, Germany, the United Kingdom, China, and Japan by a new Grey Bernoulli model. Analytical formulations of the time response function, restored values, and linear parameters estimation are derived. Further, the nonlinear parameter is determined by the Particle Swarm Optimization algorithm based on the linearized form of the model. Three numerical cases are considered to verify the effectiveness of the model. Finally, with observations from 2005 to 2017 claimed by British Petroleum Statistical Review of World Energy 2018, this new model is built to compute the natural gas consumption of the selected countries from 2018 to 2022. The numerical results show that the natural gas consumption will be increasing in the coming years. (C) 2020 Elsevier Inc. All rights reserved.

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