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      Big Data Technology in the Macrodecision-Making Model of Regional Industrial Economic Information Applied Research

      research-article
      Computational Intelligence and Neuroscience
      Hindawi

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          Abstract

          In the era of Internet +, modern industry has developed rapidly, the network economy has promoted the great development of the industrial economy, and the traditional industrial economic statistics method has not been suitable for the development needs of modern enterprises. In today's society, it can be described as the era of big data, the use of big data technology for industrial economic statistics is needed for the development of industrial modernization, and it is also a new requirement for industrial economic statistics put forward by social development. With the wide application of Internet of Things, cloud computing, mobile Internet, remote sensing, and geographic information technology in the economic field, precise economic policies have gradually developed and matured. Especially for different industries in the regional economy, according to the big data in the region, the big data mining technology and analysis technology can be used to obtain the development situation and future trend of the industrial economy in a timely and effective manner. Applying big data technology to macrodecision of regional economic information is an effective way to make macrodecision of current economy. Based on this background, this paper proposes a macroeconomic decision-making method for regional industries based on big data technology. Using data mining technology, time series data analysis methods combined with artificial intelligence analysis, the development trend of regional industries is obtained, and then the development trend of the industry is obtained. Development makes macroeconomic decisions. Taking agriculture as an example, the most popular analysis of the price trend of a certain agricultural product provides an effective reference for the development strategy of this agricultural product. The results show that the method proposed in this paper can effectively apply big data technology to the macrodecision-making of regional industrial economy. And it has better promotion significance.

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          Evaluating the impact of big data analytics usage on the decision-making quality of organizations

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            Privacy-preserving big data analytics for cyber-physical systems

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              Crisis Decision-Making at the Speed of COVID-19: Field Report on Issuing the First Regional Shelter-in-Place Orders in the United States

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                Author and article information

                Contributors
                Journal
                Comput Intell Neurosci
                Comput Intell Neurosci
                cin
                Computational Intelligence and Neuroscience
                Hindawi
                1687-5265
                1687-5273
                2022
                18 July 2022
                : 2022
                : 7400797
                Affiliations
                Shengda Economics, Trade and Management College of Zhengzhou, Zhengzhou 451191, China
                Author notes

                Academic Editor: Zhao Kaifa

                Author information
                https://orcid.org/0000-0001-8227-7318
                Article
                10.1155/2022/7400797
                9313906
                35898787
                88ea7ee4-656a-4aa6-bbe1-ab068364b3f4
                Copyright © 2022 Kaiyan Lin.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 23 May 2022
                : 29 June 2022
                Funding
                Funded by: Shengda Trade Economics and Management College of Zhengzhou
                Categories
                Research Article

                Neurosciences
                Neurosciences

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