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Energy Consumption Predication in China Based on the Modified Fractional Grey Prediction Model
Author(s) -
Jiefang Liu,
Pumei Gao
Publication year - 2021
Publication title -
journal of mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.252
H-Index - 13
eISSN - 2314-4785
pISSN - 2314-4629
DOI - 10.1155/2021/2477964
Subject(s) - energy consumption , consumption (sociology) , energy (signal processing) , process (computing) , mathematical optimization , production (economics) , econometrics , mathematics , china , computer science , statistics , economics , engineering , social science , sociology , electrical engineering , macroeconomics , operating system , law , political science
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.

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