Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone
Purpose – Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaki...
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| Format: | Article |
| Language: | English |
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Emerald Publishing
2024-07-01
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| Series: | Marine Economics and Management |
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| Online Access: | https://www.emerald.com/insight/content/doi/10.1108/MAEM-03-2024-0005/full/pdf |
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| _version_ | 1846127721294331904 |
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| author | Yuyu Sun Yuchen Zhang Zhiguo Zhao |
| author_facet | Yuyu Sun Yuchen Zhang Zhiguo Zhao |
| author_sort | Yuyu Sun |
| collection | DOAJ |
| description | Purpose – Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaking and port construction. Design/methodology/approach – Considering the effects of data randomization, this paper proposes a novel self-adaptive grey multivariate prediction model, namely FDCGM(1,N). First, fractional-order accumulative generation operation (AGO) is introduced, which integrates the policy impact effect. Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models. Findings – In the Tianjin and Fujian cases, the new model outperforms the other comparison models, with the least mean absolute percentage error (MAPE) values of 6.07% and 4.16% in the simulation phase, and 6.70% and 1.63% in the forecasting phase, respectively. The results of the comparative analysis find that after the constitution of the FTZs, Tianjin’s port cargo throughput has shown a slow growth trend, and Fujian’s port cargo throughput has exhibited rapid growth. Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years. Practical implications – The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. Meanwhile, FTZ policy has regional heterogeneity in port development, and the government can take different measures to improve the development of ports. Originality/value – Under the background of FTZ policy, the new multivariable model can be used to achieve accurate prediction, which is conducive to determining the direction of port development and planning the port layout. |
| format | Article |
| id | doaj-art-1ae7e5eec98a4a2d97fa42d405a96d8e |
| institution | Kabale University |
| issn | 2516-158X |
| language | English |
| publishDate | 2024-07-01 |
| publisher | Emerald Publishing |
| record_format | Article |
| series | Marine Economics and Management |
| spelling | doaj-art-1ae7e5eec98a4a2d97fa42d405a96d8e2024-12-11T11:41:39ZengEmerald PublishingMarine Economics and Management2516-158X2024-07-01717910110.1108/MAEM-03-2024-0005Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade ZoneYuyu Sun0Yuchen Zhang1Zhiguo Zhao2School of Economics, Ocean University of China, Qingdao, ChinaSchool of Economics, Ocean University of China, Qingdao, ChinaSchool of Economics, Ocean University of China, Qingdao, ChinaPurpose – Considering the impact of the Free Trade Zone (FTZ) policy on forecasting the port cargo throughput, this paper constructs a fractional grey multivariate forecasting model to improve the prediction accuracy of port cargo throughput and realize the coordinated development of FTZ policymaking and port construction. Design/methodology/approach – Considering the effects of data randomization, this paper proposes a novel self-adaptive grey multivariate prediction model, namely FDCGM(1,N). First, fractional-order accumulative generation operation (AGO) is introduced, which integrates the policy impact effect. Second, the heuristic grey wolf optimization (GWO) algorithm is used to determine the optimal nonlinear parameters. Finally, the novel model is then applied to port scale simulation and forecasting in Tianjin and Fujian where FTZs are situated and compared with three other grey models and two machine learning models. Findings – In the Tianjin and Fujian cases, the new model outperforms the other comparison models, with the least mean absolute percentage error (MAPE) values of 6.07% and 4.16% in the simulation phase, and 6.70% and 1.63% in the forecasting phase, respectively. The results of the comparative analysis find that after the constitution of the FTZs, Tianjin’s port cargo throughput has shown a slow growth trend, and Fujian’s port cargo throughput has exhibited rapid growth. Further, the port cargo throughput of Tianjin and Fujian will maintain a growing trend in the next four years. Practical implications – The new multivariable grey model can effectively reduce the impact of data randomness on forecasting. Meanwhile, FTZ policy has regional heterogeneity in port development, and the government can take different measures to improve the development of ports. Originality/value – Under the background of FTZ policy, the new multivariable model can be used to achieve accurate prediction, which is conducive to determining the direction of port development and planning the port layout.https://www.emerald.com/insight/content/doi/10.1108/MAEM-03-2024-0005/full/pdfPort cargo throughoutFree Trade Zone policyFDCGM(1,N) modelDummy variableFractional orderGrey wolf optimizer |
| spellingShingle | Yuyu Sun Yuchen Zhang Zhiguo Zhao Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone Marine Economics and Management Port cargo throughout Free Trade Zone policy FDCGM(1,N) model Dummy variable Fractional order Grey wolf optimizer |
| title | Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone |
| title_full | Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone |
| title_fullStr | Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone |
| title_full_unstemmed | Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone |
| title_short | Research and application of a novel grey multivariable model in port scale prediction under the impact of Free Trade Zone |
| title_sort | research and application of a novel grey multivariable model in port scale prediction under the impact of free trade zone |
| topic | Port cargo throughout Free Trade Zone policy FDCGM(1,N) model Dummy variable Fractional order Grey wolf optimizer |
| url | https://www.emerald.com/insight/content/doi/10.1108/MAEM-03-2024-0005/full/pdf |
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