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Rearch on AI industry prediction based on Markov model

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Published:17 January 2023Publication History

ABSTRACT

Artificial intelligence has become the core driving force of a new round of industrial transformation, and scientific and accurate artificial intelligence industry development prediction is of great strategic significance for improving the quality of industrial development and future industrial chain development planning. Taking the development of artificial intelligence industry in Tianjin as an example, the future development trend of artificial intelligence industry is predicted and analyzed by the quantitative comparison and analysis of Markov linear programming mathematical model. Using variable substitution method, the quadratic programming model is transformed into a linear programming model, which not only has mature solution software, but also can be solved analytically, which is more convenient and reliable. The Markov property programming model reduces the time, simplifies the complexity, reduces the difficulty of model solving, and the prediction accuracy value is high, with the average error value accounting for 2.96%, 2.07%, and 5.03%. Finally, combined with the artificial intelligence refinement industry, the countermeasures to cultivate and accelerate the development of artificial intelligence industry in Tianjin are discussed from three levels: basic industry support, technology industry innovation and application industry expansion.

References

  1. WANG Yanyu, GAO Fang. Planning model and enlightenment of artificial intelligence technology development roadmap in major countries[J].China Science and Technology Forum,2022(1):180-188.)Google ScholarGoogle Scholar
  2. Guan Haoyuan, Ao Qing. The enlightenment of foreign advanced regional experience to the innovation and development of artificial intelligence industry in Guangdong[J].Science and Technology Entrepreneurship Monthly,2018,31(3):138-142.)Google ScholarGoogle Scholar
  3. Shou Weiyi, Zhang Zhengping, Pan Xuedong Research on the development status and countermeasures of artificial intelligence industry in Hangzhou[J].Hangzhou Science and Technology,2017,0(2):11-15.)Google ScholarGoogle Scholar
  4. LIU Gang,DU Shuang. A Regional Comparative Study on the Development Mechanism of Artificial Intelligence Technology Industry in China——Value Network Analysis Based on the Sample of Intelligent Enterprises in Beijing, Hangzhou and Shenzhen[J].Journal of Social Sciences,2021(1):107-117.)Google ScholarGoogle Scholar
  5. Li Dunxiang, Li Zhixian. Analysis and prediction of tertiary industrial structure in Guangxi based on component data analysis[J].Journal of Anhui Agricultural Sciences,2011,39(09):5669-5670.DOI:10.13989/j.cnki.0517-6611.2011.09.106.Google ScholarGoogle ScholarCross RefCross Ref
  6. Zhao Dan. An empirical study on industrial structure upgrading and economic growth in underdeveloped western regions based on Markov theory[J].Practice and Understanding of Mathematics,2019,49(22):9-15.)Google ScholarGoogle Scholar
  7. Lv Jiehua,Liu Yandi,Wang Xiaohan. Prediction of Forestry Industry Structure Change Trend Based on Grey Markov Model: A Case Study of State-owned Forest Area in Heilongjiang Province[J].Journal of Central South University of Forestry and Technology,2019,39(09):122-128.DOI:10.14067/j.cnki.1673-923x.2019.09.020.Google ScholarGoogle ScholarCross RefCross Ref
  8. A. Nayak and K. Dutta, "Impacts of machine learning and artificial intelligence on mankind," 2017 International Conference on Intelligent Computing and Control (I2C2), 2017, pp. 1-3, doi: 10.1109/I2C2.2017.8321908.Google ScholarGoogle ScholarCross RefCross Ref
  9. B. Li, J. Gu and W. Jiang, "Artificial Intelligence (AI) Chip Technology Review," 2019 International Conference on Machine Learning, Big Data and Business Intelligence (MLBDBI), 2019, pp. 114-117, doi: 10.1109/MLBDBI48998.2019.00028.Google ScholarGoogle ScholarCross RefCross Ref
  10. Ahmad , "The Challenges of Artificial Intelligence in Wireless Networks for the Internet of Things: Exploring Opportunities for Growth," in IEEE Industrial Electronics Magazine, vol. 15, no. 1, pp. 16-29, March 2021, doi: 10.1109/MIE.2020.2979272.Google ScholarGoogle ScholarCross RefCross Ref
  11. Alhayani, B., Kwekha-Rashid, A.S., Mahajan, H.B. 5G standards for the Industry 4.0 enabled communication systems using artificial intelligence: perspective of smart healthcare system. Appl Nanosci (2022). https://doi.org/10.1007/s13204-021-02152-4Google ScholarGoogle ScholarCross RefCross Ref
  12. Wisteria. "China New Generation Artificial Intelligence Technology Industry Development Report 2021"[N]. Financial Times, 2021-10-25(011). DOI:10.28460/n.cnki.njrsb.2021.005528Google ScholarGoogle ScholarCross RefCross Ref

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                cover image ACM Other conferences
                AISS '22: Proceedings of the 4th International Conference on Advanced Information Science and System
                November 2022
                396 pages
                ISBN:9781450397933
                DOI:10.1145/3573834

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                Publication History

                • Published: 17 January 2023

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