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RETRACTED ARTICLE: Research on control strategy and policy optimal scheduling based on an improved genetic algorithm

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This article was retracted on 28 December 2022

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Abstract

With the rapid development of artificial intelligence and continuous in-depth integration with big data, cloud computing, robotics, and the Internet, especially the Internet of Things and blockchain, the reconstruction of society has been accelerated. This process not only enables epidemic prevention and control, economic transformation and growth, social governance reform and upgrading, and improvement in people's well-being but also puts forward many new challenges to social governance. The development of artificial intelligence must require the establishment of ethical standards and systems to be at the same frequency, and the development speed of the two must be coordinated to ensure the healthy development of technology. However, artificial intelligence not only brings convenience to people's lives but also raises people's concerns about its ramifications. To understand the influence of AI on governance in the algorithm dimension, a model of the influence of AI governance is built by using a parallel algorithm. It is necessary to learn new knowledge of social governance in the era of artificial intelligence and establish concomitant new ideas of social governance to explore a new way of social governance in the era of artificial intelligence. The research results show that after the introduction of artificial intelligence embedded governance, the governance level is greatly improved, the problem solving rate is increased by more than 50%, the satisfaction of the masses is increased by 30%, and the governance cost is reduced by 20%. However, people do not know much about the risks of artificial intelligence. Only approximately 10% of the population has a clear understanding of the risks of artificial intelligence. The research results show that artificial intelligence can play an important role in governance, but it is necessary to prevent the risks of artificial intelligence to better promote social development.

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Acknowledgements

This work was supported by Special Soft Science Project of Technological Innovation of Hubei Province (2019ADC103); Hubei Province Philosophy Social Sciences Program (19Q116); Hubei Normal University Scientific Research Innovation Team Plans (2019CP01). This work was supported by Hubei University of Economics Scientific Research Cultivate Project.

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Authors and Affiliations

  1. School of Economics Management and Law, Hubei Normal University, Huangshi, 435002, Hubei, China

    Jing Xia & Yongcai Yan

  2. School of Law, Hubei University of Economics, Wuhan, 430205, Hubei, China

    Lei Ji

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  1. Jing Xia
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  2. Yongcai Yan
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  3. Lei Ji
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Correspondence to Lei Ji.

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This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s00521-022-08191-4

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Xia, J., Yan, Y. & Ji, L. RETRACTED ARTICLE: Research on control strategy and policy optimal scheduling based on an improved genetic algorithm. Neural Comput & Applic 34, 9485–9497 (2022). https://doi.org/10.1007/s00521-021-06415-7

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  • DOI: https://doi.org/10.1007/s00521-021-06415-7

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