Author(s)

Chengbo Jin ¹

Affiliation(s)

¹ Heilongjiang Weizhong Investment Group Co., Ltd, Harbin, 150000, China

Corresponding Author

Chengbo Jin

ABSTRACT

With the rapid development of technology, artificial intelligence (AI) has become an important force leading social progress. Especially in the field of computer network technology (CNT), the integration of AI technology has brought revolutionary changes to the optimization of network performance. CNT, as the infrastructure of modern society, is closely connected to people's daily life and work. However, with the expansion of network scale and the increase in complexity, how to ensure the efficient and stable operation of the network has become an urgent problem to be solved. At this point, the introduction of AI technology becomes particularly important. In network management, AI can optimize the allocation of network resources and quickly locate faults through intelligent analysis, prediction, and automated processing, greatly improving the efficiency and accuracy of network management. Meanwhile, intelligent firewalls and intrusion detection systems utilize AI technology to identify and intercept network attacks in real-time, effectively protecting network security. In addition, AI has also played a crucial role in the innovative development of CNTs. The integration of AI technology not only promotes innovation in network technology, but also promotes the development of related industries, bringing huge economic benefits to society.

KEYWORDS

Artificial intelligence, computer network technology, innovative development, and improved economic benefits

CITE THIS PAPER

Chengbo Jin, The Application of Artificial Intelligence in the Innovation and Development of Computer Network Technology and the Improvement of Economic Benefits. Information Systems and Economics (2024) Vol. 5: 164-169. DOI: http://dx.doi.org/10.23977/infse.2024.050322.

REFERENCES

[1] Hongfei W. Research on the Application of Big Data and Artificial Intelligence Technology in Computer Network [J]. Modern Electronic Technology, 2020, 4(2): 21-22.
[2] Hua T, Li L. Computer network security technology based on artificial intelligence [J]. Journal of Intelligent & Fuzzy Systems, 2019, 37(5): 6021-6028.
[3] Ayass T, Coqueiro T, Tássio Carvalho, et al. Unmanned aerial vehicle with handover management fuzzy system for 5G networks: challenges and perspectives [J]. Intelligence & Robotics, 2022, 2(1):20-36.
[4] Lee S, Hwang J, Cho E. Comparing technology convergence of artificial intelligence on the industrial sectors: two-way approaches on network analysis and clustering analysis [J]. Scientometrics, 2022, 127(1):407-452.
[5] Gutierrez-Estevez D M, Gramaglia M, De Domenico A, et al. Artificial intelligence for elastic management and orchestration of 5G networks[J]. IEEE wireless communications, 2019, 26(5): 134-141.
[6] Wang H F, Zhang C Y, Lin D Y, et al. An artificial intelligence based method for evaluating power grid node importance using network embedding and support vector regression [J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(6):816-828.
[7] Bega D, Gramaglia M, Garcia-Saavedra A, et al. Network Slicing Meets Artificial Intelligence: An AI-Based Framework for Slice Management[J]. IEEE Communications Magazine, 2020, 58(6):32-38.
[8] Lin M, Zhao Y. Artificial intelligence-empowered resource management for future wireless communications: A survey [J]. China Communications, 2020, 17(3):58-77.
[9] Alohali M A, Al-Wesabi F N, Hilal A M, et al. Artificial intelligence enabled intrusion detection systems for cognitive cyber-physical systems in industry 40 environment [J]. Cognitive neurodynamics, 2022, 16(5):1045-1057.
[10] Ran L. Influence of government subsidy on high-tech enterprise investment based on artificial intelligence and fuzzy neural network[J]. Journal of Intelligent and Fuzzy Systems, 2021, 40(2):2553-2563.
[11] Xu X. Link optimization of the new generation instant messaging network based on artificial intelligence technology [J]. Journal of Intelligent & Fuzzy Systems, 2021, 40(4): 6113-6124.
[12] Chen F, Chen F, Liao F, et al. Dynamic governance of social network based on dynamic optimisation algorithm: a new perspective of AI system[J]. International Journal of Technology Management, 2020, 84(1-2): 25-49.
[13] Ping W. Data mining and XBRL integration in management accounting information based on artificial intelligence [J]. Journal of Intelligent and Fuzzy Systems, 2020, 40(1):1-12. 
[14] Barros M T, Velez G, Arregui H, et al. CogITS: cognition‐enabled network management for 5G V2X communication [J]. IET Intelligent Transport Systems, 2020, 14(3): 182-189.
[15] Ateya A A, Soliman N F, Alkanhel R, et al. Lightweight Deep Learning-Based Model for Traffic Prediction in Fog-Enabled Dense Deployed IoT Networks[J]. Journal of Electrical Engineering & Technology, 2022, 18(3):2275-2285.
[16] Zainaddin D A, Hanapi Z M, Othman M, et al. Recent trends and future directions of congestion management strategies for routing in IoT-based wireless sensor network: a thematic review [J]. Wireless Networks, 2024, 30(3):1939-1983.
[17] Zhao Y, Li Y, Zhang X, et al. A Survey of Networking Applications Applying the Software Defined Networking Concept Based on Machine Learning [J]. IEEE Access, 2019, 7(99):95397-95417.

Sponsors, Associates, and Links

---

• Accounting, Auditing and Finance
  
  
• Industrial Engineering and Innovation Management
  
  
• Tourism Management and Technology Economy
  
  
• Journal of Computational and Financial Econometrics
  
  
• Financial Engineering and Risk Management
  
  
• Accounting and Corporate Management
  
  
• Social Security and Administration Management
  
  
• Population, Resources & Environmental Economics
  
  
• Statistics & Quantitative Economics
  
  
• Agricultural & Forestry Economics and Management
  
  
• Social Medicine and Health Management
  
  
• Land Resource Management
  
  
• Information, Library and Archival Science
  
  
• Journal of Human Resource Development
  
  
• Manufacturing and Service Operations Management
  
  
• Operational Research and Cybernetics