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Issue title: Complex evolutionary artificial intelligence in cognitive digital twinning
Guest editors: Neal Wagner, Sundhararajan, Le Hoang Son and Meng Joo
Article type: Research Article
Affiliations: [a] School of Management, Hefei University of Technology, Hefei, China | [b] School of Management, Anhui Jianzhu University, Hefei, China
Correspondence: [*] Corresponding author. Li Ran, School of Management, Hefei University of Technology, Hefei, China. E-mail: [email protected].
Abstract: Government subsidies have an important impact on the development of high-interest technology companies and technological innovation. In order to study the relationship between government investment and the development of high-tech enterprises and technological innovation, based on artificial intelligence and fuzzy neural network, this paper builds an analysis model based on artificial intelligence and fuzzy neural network. According to the operation of each loop, this study designs a scheduling strategy that dynamically allocates network utilization according to the dynamic weight of the loop, and periodically changes the sampling period of the system, so that the system can not only run stably but also maximize the use of limited bandwidth. The network resource allocation module allocates the available network bandwidth of each control loop according to the dynamic weight of each loop, and the sampling period calculation module calculates a new sampling period based on the allocated network utilization rate. In addition, in this study, the performance of the model constructed in this paper is analyzed through empirical analysis. The results of the study show that the model constructed in this paper is effective.
Keywords: Artificial intelligence, fuzzy algorithm, government subsidies, high-tech, investment
DOI: 10.3233/JIFS-189248
Journal: Journal of Intelligent & Fuzzy Systems, vol. 40, no. 2, pp. 2553-2563, 2021
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