Energy Consumption Predication in China Based on the Modified Fractional Grey Prediction Model
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...
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Format: | Article |
Language: | English |
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Wiley
2021-01-01
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Series: | Journal of Mathematics |
Online Access: | http://dx.doi.org/10.1155/2021/2477964 |
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author | Jiefang Liu Pumei Gao |
author_facet | Jiefang Liu Pumei Gao |
author_sort | Jiefang Liu |
collection | DOAJ |
description | 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. |
format | Article |
id | doaj-art-09e8cfa6583245e6a0dfdce3580d0f9f |
institution | Kabale University |
issn | 2314-4629 2314-4785 |
language | English |
publishDate | 2021-01-01 |
publisher | Wiley |
record_format | Article |
series | Journal of Mathematics |
spelling | doaj-art-09e8cfa6583245e6a0dfdce3580d0f9f2025-02-03T07:24:24ZengWileyJournal of Mathematics2314-46292314-47852021-01-01202110.1155/2021/24779642477964Energy Consumption Predication in China Based on the Modified Fractional Grey Prediction ModelJiefang Liu0Pumei Gao1School of Management and Economics, Tianjin University of Technology and Education, Tianjin 300222, ChinaDepartment of Economics and Management, Tianjin Electronic Information College, Tianjin 300350, ChinaChina’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.http://dx.doi.org/10.1155/2021/2477964 |
spellingShingle | Jiefang Liu Pumei Gao Energy Consumption Predication in China Based on the Modified Fractional Grey Prediction Model Journal of Mathematics |
title | Energy Consumption Predication in China Based on the Modified Fractional Grey Prediction Model |
title_full | Energy Consumption Predication in China Based on the Modified Fractional Grey Prediction Model |
title_fullStr | Energy Consumption Predication in China Based on the Modified Fractional Grey Prediction Model |
title_full_unstemmed | Energy Consumption Predication in China Based on the Modified Fractional Grey Prediction Model |
title_short | Energy Consumption Predication in China Based on the Modified Fractional Grey Prediction Model |
title_sort | energy consumption predication in china based on the modified fractional grey prediction model |
url | http://dx.doi.org/10.1155/2021/2477964 |
work_keys_str_mv | AT jiefangliu energyconsumptionpredicationinchinabasedonthemodifiedfractionalgreypredictionmodel AT pumeigao energyconsumptionpredicationinchinabasedonthemodifiedfractionalgreypredictionmodel |