Energy Consumption Predication in China Based on the Modified Fractional Grey Prediction Model

Jiefang Liu, Pumei Gao and Shuhua Mao

Journal of Mathematics, 2021, vol. 2021, 1-7

Abstract: China’s increasing energy consumption poses challenges to economy and environment. How to predict the energy consumption accurately and regulate the future energy consumption production is a problem worth studying. In this paper, the fractional order cumulative linear time-varying parameter discrete grey prediction model (FTDGM (1, 1) model) is introduced. Firstly, the data are preprocessed by buffer operators, and then, the FTDGM (1, 1) model is established. In this paper, the parameter estimation method and the specific process of model establishment are presented. Finally, the models of energy consumption in China are built. The advantages and prediction accuracy of the model established in this paper are analyzed, and the data in the following years are effectively predicted, so as to provide theoretical support for the government to formulate reasonable energy policies.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jjmath:2477964

DOI: 10.1155/2021/2477964

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