The development trend of China’s marine economy: a predictive analysis based on industry level
This paper aims to provide insights into the future trends for the marine industries in China, by forecasting the added value in key sectors and then offering tailored policy recommendations. Those economic indicators at the industry level are characterized by small sample sizes, sectoral heterogene...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Marine Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmars.2025.1544612/full |
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| author | Yu Chen Huahan Zhang Lingling Pei |
| author_facet | Yu Chen Huahan Zhang Lingling Pei |
| author_sort | Yu Chen |
| collection | DOAJ |
| description | This paper aims to provide insights into the future trends for the marine industries in China, by forecasting the added value in key sectors and then offering tailored policy recommendations. Those economic indicators at the industry level are characterized by small sample sizes, sectoral heterogeneity, and irregular fluctuations, which require a specialized methodology to handle data features and provide predictions for each industry. To address these issues, the conformable fractional grey model (CFGM), which integrates conformable fractional accumulation with the grey forecasting model, is applied and proven effective through accuracy and robustness tests. First, the results from multi-step experiments demonstrate that the CFGM model significantly outperforms traditional statistical, machine learning models, and grey models in the context of the sectoral added value predictions, with an average accuracy improvement of 32.14%. Second, the robustness and stability of the predictive values generated by CFGM are further verified by the Probability Density Analysis (PDA) and multiple comparisons with the best (MCB) tests, thereby ruling out the possibility that these accurate predictions are the result of mere chance. Third, the CFGM model is used to estimate the future added values across multiple marine industries, accompanied by suggestions to ensure the sustainable development of the marine economy. |
| format | Article |
| id | doaj-art-6582e9ecae364e4c83349b922627adf0 |
| institution | Kabale University |
| issn | 2296-7745 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Marine Science |
| spelling | doaj-art-6582e9ecae364e4c83349b922627adf02025-02-10T11:08:59ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452025-02-011210.3389/fmars.2025.15446121544612The development trend of China’s marine economy: a predictive analysis based on industry levelYu Chen0Huahan Zhang1Lingling Pei2Reading Academy, Nanjing University of Information Science and Technology, Nanjing, ChinaSchool of Economics, Zhejiang University of Finance and Economics, Hangzhou, ChinaSchool of Management, Zhejiang University of Finance and Economics, Hangzhou, ChinaThis paper aims to provide insights into the future trends for the marine industries in China, by forecasting the added value in key sectors and then offering tailored policy recommendations. Those economic indicators at the industry level are characterized by small sample sizes, sectoral heterogeneity, and irregular fluctuations, which require a specialized methodology to handle data features and provide predictions for each industry. To address these issues, the conformable fractional grey model (CFGM), which integrates conformable fractional accumulation with the grey forecasting model, is applied and proven effective through accuracy and robustness tests. First, the results from multi-step experiments demonstrate that the CFGM model significantly outperforms traditional statistical, machine learning models, and grey models in the context of the sectoral added value predictions, with an average accuracy improvement of 32.14%. Second, the robustness and stability of the predictive values generated by CFGM are further verified by the Probability Density Analysis (PDA) and multiple comparisons with the best (MCB) tests, thereby ruling out the possibility that these accurate predictions are the result of mere chance. Third, the CFGM model is used to estimate the future added values across multiple marine industries, accompanied by suggestions to ensure the sustainable development of the marine economy.https://www.frontiersin.org/articles/10.3389/fmars.2025.1544612/fullgrey forecasting modelmarine economic predictionmarine sustainable developmentmarine industry strategic planpolicy analyses |
| spellingShingle | Yu Chen Huahan Zhang Lingling Pei The development trend of China’s marine economy: a predictive analysis based on industry level Frontiers in Marine Science grey forecasting model marine economic prediction marine sustainable development marine industry strategic plan policy analyses |
| title | The development trend of China’s marine economy: a predictive analysis based on industry level |
| title_full | The development trend of China’s marine economy: a predictive analysis based on industry level |
| title_fullStr | The development trend of China’s marine economy: a predictive analysis based on industry level |
| title_full_unstemmed | The development trend of China’s marine economy: a predictive analysis based on industry level |
| title_short | The development trend of China’s marine economy: a predictive analysis based on industry level |
| title_sort | development trend of china s marine economy a predictive analysis based on industry level |
| topic | grey forecasting model marine economic prediction marine sustainable development marine industry strategic plan policy analyses |
| url | https://www.frontiersin.org/articles/10.3389/fmars.2025.1544612/full |
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