A CRITIC-TOPSIS and optimized nonlinear grey prediction model: A comparative convergence analysis of marine economic resilience

被引:5
|
作者
Li, Xuemei [1 ,2 ]
Zhou, Shiwei [1 ,2 ]
Zhao, Yufeng [2 ,3 ]
Wan, Guangxue [4 ]
机构
[1] Ocean Univ China, Sch Econ, Qingdao 266100, Peoples R China
[2] Ocean Univ China, Inst Marine Dev, Qingdao 266100, Peoples R China
[3] Ocean Univ China, Sch Management, Qingdao 266100, Peoples R China
[4] Shandong Univ, Sch Business, Weihai 264209, Peoples R China
基金
中国国家自然科学基金;
关键词
Marine economic resilience; Regional disparity; Convergence analysis; Spatio-temporal evolution; Grey prediction model; Grey wolf optimization; ENERGY-CONSUMPTION; SIGMA-CONVERGENCE; GROWTH; REGIONS;
D O I
10.1016/j.eswa.2023.121356
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The strength of marine economic resilience (MER) determines whether a region can maintain its original development path or fall into stagnation in the face of economic shock, which is an important starting point for promoting marine economic sustainable development. We discuss the connotation and propose a logical framework for MER, which is estimated by CRITIC-TOPSIS method from 2006 to 2019 based on three dimensions (country, region, province). Furthermore, the temporal evolution trend and regional disparities are accessed by Dagum Gini coefficient. Results reveal that MER has shown a significant upward trend, and it is undergoing gradient change in China, and unfortunately, the specific performance is in the imbalance, and lack of coordination of MER in the southern marine economic circle is the most prominent. Foreseeably, the novel fractional nonlinear grey model with double optimization (DOFNGBM(1,1)) combining Grey wolf optimization (GWO) algorithm is proposed and its performance is examined. Ulteriorly, as predicted by DOFNGBM(1,1) and presented by & sigma; convergence and & beta; convergence models, based on the cross-comparison between in-sample and out-ofsample, significant findings indicate that weak convergence of China's MER indicates that coastal areas with a low level have faster improvement rates, and MER in China will present different ways of growing delightedly. Comparatively, considering the driving factors of marine economic resilience, all of them are proven to be conducive to raising the steady-state value of MER to a higher level, despite the regional heterogeneity of their effects. Purposefully, it implies that diversified development and synergistic cooperation can improve the endogenous power of marine economic resilience.
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页数:22
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  • [1] Economic Benefit Evaluation Analysis for Distributed Energy Generation Projects Based on CRITIC-TOPSIS model
    Yang, Yongqi
    Li, Chaoyuan
    Xue, Wanlei
    Kang, Shuyu
    [J]. 2018 4TH INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND MATERIAL APPLICATION, 2019, 252
  • [2] An entropy-based TOPSIS and optimized grey prediction model for spatiotemporal analysis in strategic emerging industry
    Ding, Song
    Li, Ruojin
    Guo, Junha
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2023, 213
  • [3] A ROLLING GREY MODEL OPTIMIZED BY PARTICLE SWARM OPTIMIZATION IN ECONOMIC PREDICTION
    Liu, Li
    Wang, Qianru
    Wang, Jianzhou
    Liu, Ming
    [J]. COMPUTATIONAL INTELLIGENCE, 2016, 32 (03) : 391 - 419
  • [4] A nonlinear hyperbolic optimized grey model for market clearing price prediction: Analysis and case study
    Saxena, Akash
    [J]. SUSTAINABLE ENERGY GRIDS & NETWORKS, 2024, 38
  • [5] An optimized nonlinear grey Bernoulli prediction model and its application in natural gas production
    Liu, Chong
    Lao, Tongfei
    Wu, Wen-Ze
    Xie, Wanli
    Zhu, Hegui
    [J]. EXPERT SYSTEMS WITH APPLICATIONS, 2022, 194
  • [6] Prediction and analysis of domestic water consumption based on optimized grey and Markov model
    Wang, Zhaocai
    Wu, Xian
    Wang, Huifang
    Wu, Tunhua
    [J]. WATER SUPPLY, 2021, 21 (07) : 3887 - 3899
  • [7] A novel conformable fractional nonlinear grey multivariable prediction model with marine predator algorithm for time series prediction
    Zhu, Hegui
    Liu, Chong
    Wu, Wenze
    Xie, Wanli
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2023, 180
  • [8] Novel grey prediction model with nonlinear optimized time response method for forecasting of electricity consumption in China
    Xu, Ning
    Dang, Yaoguo
    Gong, Yande
    [J]. ENERGY, 2017, 118 : 473 - 480
  • [9] Convergence analysis of urban green traffic carbon emission based on grey prediction model
    Niu, Lede
    Pan, Mei
    Xiong, Liran
    [J]. INTERNATIONAL JOURNAL OF GLOBAL ENERGY ISSUES, 2020, 42 (5-6) : 285 - 301
  • [10] An optimized Nash nonlinear grey Bernoulli model for forecasting the main economic indices of high technology enterprises in China
    Wang, Zheng-Xin
    [J]. COMPUTERS & INDUSTRIAL ENGINEERING, 2013, 64 (03) : 780 - 787