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Industrial Economy and Regional Growth Strategy Based on Particle Swarm Optimization Algorithm

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Innovative Computing Vol 1 - Emerging Topics in Artificial Intelligence (IC 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1044))

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Abstract

With the rapid growth of the global economy, it has become an inevitable trend for Chinese enterprises to transform and upgrade their industries. This paper starts with the research status at home and abroad, and analyzes the problems existing in the current industrial growth of China in combination with relevant literature and cases in the industry. Then, through the research of particle swarm optimization (PSO) algorithm, the growth trajectory of major cities in China and the regional competition status of each region are summarized. Finally, the PSO algorithm is applied to the optimization solution model of the location of industries in various provinces and cities in China based on the regional economic and social growth strategy, and the final results are obtained. The results show that the coordinated growth coefficient and comprehensive growth level are about 5 and 7 in this model, The level of coordinated growth is shown in 5 test results. Therefore, the industrial economy and regional growth strategy model based on PSO algorithm meets the needs of users.

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Funding

This work was supported by Special Fund project of National Natural Science Foundation of China (42130712); GDAS Special Project of Science and Technology Development (2020GDASYL–20200102002).

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Authors and Affiliations

  1. Institute of Strategy Research for the Guangdong-Hong Kong-Macao Greater Bay Area, Guangdong Academy of Sciences, Guangzhou, 510070, Guangdong, China

    Hengran Bian & Yi Liu

  2. Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Bei**g, 100101, China

    Yi Liu

Authors
  1. Hengran Bian
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  2. Yi Liu
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Corresponding author

Correspondence to Hengran Bian .

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Editors and Affiliations

  1. Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, FIET, Taichung City, Taiwan

    Jason C. Hung

  2. Department of Computer Science and Information Engineering, National Taichung University of Science and Technology, FIET, Taichung City, Taiwan

    Jia-Wei Chang

  3. Computer Science and Engineering, University of Aizu, Aizuwakamatsu, Fukushima, Japan

    Yan Pei

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Bian, H., Liu, Y. (2023). Industrial Economy and Regional Growth Strategy Based on Particle Swarm Optimization Algorithm. In: Hung, J.C., Chang, JW., Pei, Y. (eds) Innovative Computing Vol 1 - Emerging Topics in Artificial Intelligence. IC 2023. Lecture Notes in Electrical Engineering, vol 1044. Springer, Singapore. https://doi.org/10.1007/978-981-99-2092-1_60

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  • DOI: https://doi.org/10.1007/978-981-99-2092-1_60

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-2091-4

  • Online ISBN: 978-981-99-2092-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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