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4 November 2020 Construction of Marine Economic Forecast Management System Based on Artificial Intelligence
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Abstract

Liu, Y., 2020. Construction of marine economic forecast management system based on artificial intelligence. 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. 228-230. Coconut Creek (Florida), ISSN 0749-0208.

Data is an important content in the process of economic development. In an environment where the types and quantities of data are increasing, if you want to do a good job in economic forecasting and financial analysis, you must scientifically apply big data technology and understand the current development through big data Trends and grasp the direction of market development. The marine economic forecast management system occupies an important position in the economic market development. If you want to better promote economic development, you must combine the current development form to realize the effective application of big data technology and complete economic forecasting and financial analysis on this basis. Helping the marine economic forecast management system to find development rules and clues is of great significance to the future development of the marine economic forecast management system. Big data technology has the characteristics of complexity, relevance and integrity. In practical applications, it can analyze multiple aspects of data. Each economic activity and behavior can be displayed through data information, without a single emphasis. When conducting big data analysis, it is necessary to combine industry development needs, scientifically select data algorithms and link different types of data information on this basis.

©Coastal Education and Research Foundation, Inc. 2020
Yi Liu "Construction of Marine Economic Forecast Management System Based on Artificial Intelligence," Journal of Coastal Research 112(sp1), 228-230, (4 November 2020). https://doi.org/10.2112/JCR-SI112-063.1
Received: 30 June 2020; Accepted: 3 August 2020; Published: 4 November 2020
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