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4 November 2020 The Simulation of the Prediction Model of the Economic Development Potential of the Coastal Area
Caixia Pei, Yisheng Liu
Author Affiliations +
Abstract

Pei, C. and Liu, Y., 2020. The simulation of the prediction model of the economic development potential of the coastal area. In: Li, L. and Huang, X. (eds.), Sustainable Development in Coastal Regions: A Perspective of Environment, Economy, and Technology. Journal of Coastal Research, Special Issue No. 112, pp. 211-215. Coconut Creek (Florida), ISSN 0749-0208.

Regional economic potential is affected by excessive entities and substantial dynamic changes in the economic structure. The variation proportion shows strong nonlinearity. Information redundancy and interference are present among different impact indexes. Such unexpected change can affect the forecasting results obtained based on traditional economic potential development forecasting methods, causing the problem of local optimum and relatively significant errors. With the industrial structure in the coastal region as the research object, based on the system dynamics theory, the causal relationship between the talent flow, technology flow, capital flow, and market flow is analyzed. The grey forecasting model is used to predict the spatio-temporal evolution of the industrial structure, compare different forecasting results, and analyze the main factors of industrial structure adjustment. It is proposed that the development status of the study area should be improved from the ecological, social, economic, and other aspects to achieve sustainable socio-economic development.

©Coastal Education and Research Foundation, Inc. 2020
Caixia Pei and Yisheng Liu "The Simulation of the Prediction Model of the Economic Development Potential of the Coastal Area," Journal of Coastal Research 112(sp1), 211-215, (4 November 2020). https://doi.org/10.2112/JCR-SI112-059.1
Received: 30 June 2020; Accepted: 3 August 2020; Published: 4 November 2020
KEYWORDS
grey forecast
industrial structure
sustainable development
system dynamics
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