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Prediction of Natural Gas Consumption in Different Regions of China Using a Hybrid MVO-NNGBM Model

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  • Xiaoyu Wang
  • Dongkun Luo
  • Jianye Liu
  • Wenhuan Wang
  • Guixin Jie

Abstract

The accurate and reasonable prediction of natural gas consumption is significant for the government to formulate energy planning. To this end, we use the multiverse optimizer (MVO) algorithm to optimize the parameters of the Nash nonlinear grey Bernoulli model (NNGBM (1,1)) and propose a hybrid MVO-NNGBM model to predict the natural gas consumption in 30 regions of China. The results indicate that the prediction precision of the hybrid MVO-NNGBM model is better than that of other grey-based models. According to the forecast results, China’s natural gas consumption will grow rapidly over the next five years and reach 354.1 billion cubic meters (bcm) by 2020. Moreover, the spatial distribution of natural gas consumption will shift from being supply oriented towards being demand driven and will be mainly concentrated in coastal and developed provinces.

Suggested Citation

  • Xiaoyu Wang & Dongkun Luo & Jianye Liu & Wenhuan Wang & Guixin Jie, 2017. "Prediction of Natural Gas Consumption in Different Regions of China Using a Hybrid MVO-NNGBM Model," Mathematical Problems in Engineering, Hindawi, vol. 2017, pages 1-10, November.
    • Handle: RePEc:hin:jnlmpe:6045708
    DOI: 10.1155/2017/6045708
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    Cited by:

    1. Tomasz Cieślik & Piotr Narloch & Adam Szurlej & Krzysztof Kogut, 2022. "Indirect Impact of the COVID-19 Pandemic on Natural Gas Consumption by Commercial Consumers in a Selected City in Poland," Energies, MDPI, vol. 15(4), pages 1-18, February.

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