Container Throughput Forecasting of Tianjin-Hebei Port Group Based on Grey Combination Model
Container throughput forecasting plays an important role in port capacity planning and management. Regarding the issue of container throughput of Tianjin-Hebei Port Group, considering the container throughput is an incomplete grey information system affected by various factors, the effect is often u...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Journal of Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2021/8877865 |
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| _version_ | 1850221875490193408 |
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| author | Chen He Huipo Wang |
| author_facet | Chen He Huipo Wang |
| author_sort | Chen He |
| collection | DOAJ |
| description | Container throughput forecasting plays an important role in port capacity planning and management. Regarding the issue of container throughput of Tianjin-Hebei Port Group, considering the container throughput is an incomplete grey information system affected by various factors, the effect is often unsatisfactory by adopting a single forecasting model. Therefore, this paper studies the issue by combining fractional GM (1, 1) and BP neural network. The comparison results show that the combination model performs better than other single models separately and has a higher level of forecasting accuracy. Furthermore, the combination model is adopted to forecast the container throughput of Tianjin-Hebei Port Group from 2021 to 2025, which would be a data reference for the future development optimization for the container operation of Tianjin-Hebei Port Group. |
| format | Article |
| id | doaj-art-7155d260b6694c54b610e91e40ecf539 |
| institution | OA Journals |
| issn | 2314-4629 2314-4785 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Mathematics |
| spelling | doaj-art-7155d260b6694c54b610e91e40ecf5392025-08-20T02:06:35ZengWileyJournal of Mathematics2314-46292314-47852021-01-01202110.1155/2021/88778658877865Container Throughput Forecasting of Tianjin-Hebei Port Group Based on Grey Combination ModelChen He0Huipo Wang1School of Management Engineering and Business, Hebei University of Engineering, Handan 056038, ChinaSchool of Management Engineering and Business, Hebei University of Engineering, Handan 056038, ChinaContainer throughput forecasting plays an important role in port capacity planning and management. Regarding the issue of container throughput of Tianjin-Hebei Port Group, considering the container throughput is an incomplete grey information system affected by various factors, the effect is often unsatisfactory by adopting a single forecasting model. Therefore, this paper studies the issue by combining fractional GM (1, 1) and BP neural network. The comparison results show that the combination model performs better than other single models separately and has a higher level of forecasting accuracy. Furthermore, the combination model is adopted to forecast the container throughput of Tianjin-Hebei Port Group from 2021 to 2025, which would be a data reference for the future development optimization for the container operation of Tianjin-Hebei Port Group.http://dx.doi.org/10.1155/2021/8877865 |
| spellingShingle | Chen He Huipo Wang Container Throughput Forecasting of Tianjin-Hebei Port Group Based on Grey Combination Model Journal of Mathematics |
| title | Container Throughput Forecasting of Tianjin-Hebei Port Group Based on Grey Combination Model |
| title_full | Container Throughput Forecasting of Tianjin-Hebei Port Group Based on Grey Combination Model |
| title_fullStr | Container Throughput Forecasting of Tianjin-Hebei Port Group Based on Grey Combination Model |
| title_full_unstemmed | Container Throughput Forecasting of Tianjin-Hebei Port Group Based on Grey Combination Model |
| title_short | Container Throughput Forecasting of Tianjin-Hebei Port Group Based on Grey Combination Model |
| title_sort | container throughput forecasting of tianjin hebei port group based on grey combination model |
| url | http://dx.doi.org/10.1155/2021/8877865 |
| work_keys_str_mv | AT chenhe containerthroughputforecastingoftianjinhebeiportgroupbasedongreycombinationmodel AT huipowang containerthroughputforecastingoftianjinhebeiportgroupbasedongreycombinationmodel |