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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| Format: | Article |
| Language: | English English |
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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 |
| _version_ | 1796911183237742592 |
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| author | Yunhong Xu Huadong Wang Nga, Lay Hui |
| author_facet | Yunhong Xu Huadong Wang Nga, Lay Hui |
| author_sort | Yunhong Xu |
| collection | UMS |
| 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. |
| first_indexed | 2024-03-06T03:15:02Z |
| format | Article |
| id | ums.eprints-32219 |
| institution | Universiti Malaysia Sabah |
| language | English English |
| last_indexed | 2024-03-06T03:15:02Z |
| publishDate | 2021 |
| publisher | Hindawi |
| record_format | dspace |
| spelling | 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 https://doi.org/10.1155/2021/3023385 |
| 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 |
| title | 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_short | 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 |
| topic | S1-(972) Agriculture (General) S560-571.5 Farm economics. Farm management. Agricultural mathematics Including production standards, record keeping, farmwork rates, marketing |
| 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 |
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