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Research and application of multi-variable grey optimization model with interactive effects in marine emerging industries prediction

Author

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  • Li, Xuemei
  • Wu, Xinran
  • Zhao, Yufeng

Abstract

Marine emerging industries have become an important growth point of the marine economy and a new driving force for the transformation and upgrading of the nation. Therefore, it is crucial to predict the future trend of output values of marine emerging industries for the development of the marine economy. To measure simultaneously the output value of China's three marine emerging industries (marine power industry, marine biopharmaceutical industry, and marine chemical industry) and considering the actual situation and internal connection of mutual influence and restriction among the three industries, the interaction term is introduced on the basis of the existing MGM(1,m) model, and a MGM(1,m) model with interactive effects (IMGM(1,m) model) is established. Also, the Particle Swarm Optimization (PSO) algorithm is used to optimize the predicted value in the model. The empirical results show that the MAPE of the training set is 2.04 %, 0.22 %, and 1.33 %, while those of the test set is 5.54 %, 3.68 %, and 4.80 %, respectively. The results of the proposed model are significantly better than other comparison models. Ultimately, the new model will be adopted to predict the output value of China's marine power, marine biopharmaceutical, and marine chemical industries from 2020 to 2023. It is estimated that by 2023, the output value of the three marine industries will reach 60.050, 59.790, and 84.497 billion yuan respectively, which will continue to maintain a growing trend. The forecast results will provide strong support for national policies and development plans for marine emerging industries.

Suggested Citation

  • Li, Xuemei & Wu, Xinran & Zhao, Yufeng, 2023. "Research and application of multi-variable grey optimization model with interactive effects in marine emerging industries prediction," Technological Forecasting and Social Change, Elsevier, vol. 187(C).
    • Handle: RePEc:eee:tefoso:v:187:y:2023:i:c:s0040162522007247
    DOI: 10.1016/j.techfore.2022.122203
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    as
    1. Shen, Gongming & Heino, Mikko, 2014. "An overview of marine fisheries management in China," Marine Policy, Elsevier, vol. 44(C), pages 265-272.
    2. Roche, R.C. & Walker-Springett, K. & Robins, P.E. & Jones, J. & Veneruso, G. & Whitton, T.A. & Piano, M. & Ward, S.L. & Duce, C.E. & Waggitt, J.J. & Walker-Springett, G.R. & Neill, S.P. & Lewis, M.J. , 2016. "Research priorities for assessing potential impacts of emerging marine renewable energy technologies: Insights from developments in Wales (UK)," Renewable Energy, Elsevier, vol. 99(C), pages 1327-1341.
    3. Liu, Changhao & Zhang, Kai, 2013. "Industrial ecology and water utilization of the marine chemical industry: A case study of Hai Hua Group (HHG), China," Resources, Conservation & Recycling, Elsevier, vol. 70(C), pages 78-85.
    4. Xiu-Mei Fu & Shan-Shan Jiang & Na Wang & Shi-Qi Wang & Chang-Yun Wang, 2018. "The Research on International Development Path of China’s Marine Biopharmaceutical Industry," Sustainability, MDPI, vol. 10(2), pages 1-17, February.
    5. Zhou, Weijie & Wu, Xiaoli & Ding, Song & Pan, Jiao, 2020. "Application of a novel discrete grey model for forecasting natural gas consumption: A case study of Jiangsu Province in China," Energy, Elsevier, vol. 200(C).
    6. Wang, Zheng-Xin & Jv, Yue-Qi, 2021. "A non-linear systematic grey model for forecasting the industrial economy-energy-environment system," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    7. Yang, Zhenbing & Shao, Shuai & Li, Chengyu & Yang, Lili, 2020. "Alleviating the misallocation of R&D inputs in China's manufacturing sector: From the perspectives of factor-biased technological innovation and substitution elasticity," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    8. Chen, Yan & Lifeng, Wu & Lianyi, Liu & Kai, Zhang, 2020. "Fractional Hausdorff grey model and its properties," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    9. Wang, Zheng-Xin & He, Ling-Yang & Zheng, Hong-Hao, 2019. "Forecasting the residential solar energy consumption of the United States," Energy, Elsevier, vol. 178(C), pages 610-623.
    10. Gosens, Jorrit & Lu, Yonglong, 2013. "From lagging to leading? Technological innovation systems in emerging economies and the case of Chinese wind power," Energy Policy, Elsevier, vol. 60(C), pages 234-250.
    11. Ma, Xuejiao & Jiang, Ping & Jiang, Qichuan, 2020. "Research and application of association rule algorithm and an optimized grey model in carbon emissions forecasting," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    12. Wright, Glen, 2015. "Marine governance in an industrialised ocean: A case study of the emerging marine renewable energy industry," Marine Policy, Elsevier, vol. 52(C), pages 77-84.
    13. Wu, Wen-Ze & Zeng, Liang & Liu, Chong & Xie, Wanli & Goh, Mark, 2022. "A time power-based grey model with conformable fractional derivative and its applications," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    14. Yu, Jiang & Xiao, Xiao & Zhang, Yue, 2016. "From concept to implementation: The development of the emerging cloud computing industry in China," Telecommunications Policy, Elsevier, vol. 40(2), pages 130-146.
    15. Hu, Guangyu & Rong, Ke & Shi, Yongjiang & Yu, Jing, 2014. "Sustaining the emerging carbon trading industry development: A business ecosystem approach of carbon traders," Energy Policy, Elsevier, vol. 73(C), pages 587-597.
    16. Ding, Jian & Liu, Baoliu & Shao, Xuefeng, 2022. "Spatial effects of industrial synergistic agglomeration and regional green development efficiency: Evidence from China," Energy Economics, Elsevier, vol. 112(C).
    17. Erik P. Gilje & Jerome P. Taillard, 2016. "Do Private Firms Invest Differently than Public Firms? Taking Cues from the Natural Gas Industry," Journal of Finance, American Finance Association, vol. 71(4), pages 1733-1778, August.
    18. Jeffrey, Henry & Jay, Brighid & Winskel, Mark, 2013. "Accelerating the development of marine energy: Exploring the prospects, benefits and challenges," Technological Forecasting and Social Change, Elsevier, vol. 80(7), pages 1306-1316.
    19. Sun, Xiaohua & Liu, Xiaoling & Wang, Yun & Yuan, Fang, 2019. "The effects of public subsidies on emerging industry: An agent-based model of the electric vehicle industry," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 281-295.
    20. Johan Jansson, 2011. "Emerging (internet) industry and agglomeration: Internet entrepreneurs coping with uncertainty," Entrepreneurship & Regional Development, Taylor & Francis Journals, vol. 23(7-8), pages 499-521, September.
    21. Bahers, Jean-Baptiste & Tanguy, Audrey & Pincetl, Stephanie, 2020. "Metabolic relationships between cities and hinterland: a political-industrial ecology of energy metabolism of Saint-Nazaire metropolitan and port area (France)," Ecological Economics, Elsevier, vol. 167(C).
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