Prediction of Agricultural Water Consumption in 2 Regions of China Based on Fractional-Order Cumulative Discrete GreyModel

In this paper, a new forecasting method of agricultural water demand, fractional-order cumulative discrete grey model, is proposed. Firstly, the best fitting of historical data is used to construct the optimization model. MATLAB programming is applied to solve the optimization model and obtain the o...

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Main Authors: Yunhong Xu, Huadong Wang, Nga, Lay Hui
Format: Article
Language:English
English
Published: Hindawi 2021
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Online Access:https://eprints.ums.edu.my/id/eprint/32219/1/Prediction%20of%20Agricultural%20Water%20Consumption%20in%202%20Regions%20of%20China%20Based%20on%20Fractional-Order%20Cumulative%20Discrete%20GreyModel.pdf
https://eprints.ums.edu.my/id/eprint/32219/2/Prediction%20of%20Agricultural%20Water%20Consumption%20in%202%20Regions%20of%20China%20Based%20on%20Fractional-Order%20Cumulative%20Discrete%20GreyModel1.pdf
https://eprints.ums.edu.my/id/eprint/32219/
https://www.hindawi.com/journals/jmath/2021/3023385/
https://doi.org/10.1155/2021/3023385
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Institution: Universiti Malaysia Sabah
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spelling my.ums.eprints.322192022-04-03T23:56:30Z https://eprints.ums.edu.my/id/eprint/32219/ Prediction of Agricultural Water Consumption in 2 Regions of China Based on Fractional-Order Cumulative Discrete GreyModel Yunhong Xu Huadong Wang Nga, Lay Hui S1-(972) Agriculture (General) S560-571.5 Farm economics. Farm management. Agricultural mathematics Including production standards, record keeping, farmwork rates, marketing In this paper, a new forecasting method of agricultural water demand, fractional-order cumulative discrete grey model, is proposed. Firstly, the best fitting of historical data is used to construct the optimization model. MATLAB programming is applied to solve the optimization model and obtain the optimal order. Secondly, the fractional-order cumulative discrete grey model in this paper is compared with GM (1, 1) model to verify the performance of the model. Finally, Handan region of Hebei Province and Jingzhou region of Hubei Province were selected as the study areas to predict their agricultural water consumptions. .e results show that the fractional-order cumulative discrete grey model has better prediction performance than the GM (1, 1) model. It can be used as an effective method for forecasting agricultural water consumption. Hindawi 2021 Article PeerReviewed text en https://eprints.ums.edu.my/id/eprint/32219/1/Prediction%20of%20Agricultural%20Water%20Consumption%20in%202%20Regions%20of%20China%20Based%20on%20Fractional-Order%20Cumulative%20Discrete%20GreyModel.pdf text en https://eprints.ums.edu.my/id/eprint/32219/2/Prediction%20of%20Agricultural%20Water%20Consumption%20in%202%20Regions%20of%20China%20Based%20on%20Fractional-Order%20Cumulative%20Discrete%20GreyModel1.pdf Yunhong Xu and Huadong Wang and Nga, Lay Hui (2021) Prediction of Agricultural Water Consumption in 2 Regions of China Based on Fractional-Order Cumulative Discrete GreyModel. Journal of Mathematics, 2021. pp. 1-7. ISSN 2314-4785 https://www.hindawi.com/journals/jmath/2021/3023385/ https://doi.org/10.1155/2021/3023385
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic S1-(972) Agriculture (General)
S560-571.5 Farm economics. Farm management. Agricultural mathematics Including production standards, record keeping, farmwork rates, marketing
spellingShingle S1-(972) Agriculture (General)
S560-571.5 Farm economics. Farm management. Agricultural mathematics Including production standards, record keeping, farmwork rates, marketing
Yunhong Xu
Huadong Wang
Nga, Lay Hui
Prediction of Agricultural Water Consumption in 2 Regions of China Based on Fractional-Order Cumulative Discrete GreyModel
description In this paper, a new forecasting method of agricultural water demand, fractional-order cumulative discrete grey model, is proposed. Firstly, the best fitting of historical data is used to construct the optimization model. MATLAB programming is applied to solve the optimization model and obtain the optimal order. Secondly, the fractional-order cumulative discrete grey model in this paper is compared with GM (1, 1) model to verify the performance of the model. Finally, Handan region of Hebei Province and Jingzhou region of Hubei Province were selected as the study areas to predict their agricultural water consumptions. .e results show that the fractional-order cumulative discrete grey model has better prediction performance than the GM (1, 1) model. It can be used as an effective method for forecasting agricultural water consumption.
format Article
author Yunhong Xu
Huadong Wang
Nga, Lay Hui
author_facet Yunhong Xu
Huadong Wang
Nga, Lay Hui
author_sort Yunhong Xu
title Prediction of Agricultural Water Consumption in 2 Regions of China Based on Fractional-Order Cumulative Discrete GreyModel
title_short Prediction of Agricultural Water Consumption in 2 Regions of China Based on Fractional-Order Cumulative Discrete GreyModel
title_full Prediction of Agricultural Water Consumption in 2 Regions of China Based on Fractional-Order Cumulative Discrete GreyModel
title_fullStr Prediction of Agricultural Water Consumption in 2 Regions of China Based on Fractional-Order Cumulative Discrete GreyModel
title_full_unstemmed Prediction of Agricultural Water Consumption in 2 Regions of China Based on Fractional-Order Cumulative Discrete GreyModel
title_sort prediction of agricultural water consumption in 2 regions of china based on fractional-order cumulative discrete greymodel
publisher Hindawi
publishDate 2021
url https://eprints.ums.edu.my/id/eprint/32219/1/Prediction%20of%20Agricultural%20Water%20Consumption%20in%202%20Regions%20of%20China%20Based%20on%20Fractional-Order%20Cumulative%20Discrete%20GreyModel.pdf
https://eprints.ums.edu.my/id/eprint/32219/2/Prediction%20of%20Agricultural%20Water%20Consumption%20in%202%20Regions%20of%20China%20Based%20on%20Fractional-Order%20Cumulative%20Discrete%20GreyModel1.pdf
https://eprints.ums.edu.my/id/eprint/32219/
https://www.hindawi.com/journals/jmath/2021/3023385/
https://doi.org/10.1155/2021/3023385
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