Abstract
With the progress of various software and hardware technologies, the data processing and computing power of the computer are further enhanced. Artificial intelligence technology has entered a period of rapid development. The current “Internet + ” boom and the continued prosperity of the big data industry have further accelerated the integration of artificial intelligence technology with other related industries. This paper summarizes the Internet information, static information collection technology and artificial intelligence technology, analyzes the neural network, puts forward RRT path planning, and studies the pheromone increment dynamic update strategy. The results show that when LK is less than lbest, the increase of the difference will sharply increase the pheromone increment on the path, which makes the algorithm easy to fall into local optimization.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Palade, V., Wolff, J.G.: A roadmap for the development of the ‘SP Machine’ for artificial intelligence. Comput. J. 62(11), 1584–1604 (2019)
Elkawkagy, M., Heba, E.: Reduce artificial intelligence planning effort by using map-reduce paradigm. Int. J. Innovative Technol. Exploring Eng. 10(7), 24–32 (2021)
Long, K.F.: A rapid study on the development of an interstellar roadmap and planning ahead for technology maturation. J. Br. Interplanet. Soc. 73(1), 6–14 (2020)
Deepthi, K.C.: A novel artificial intelligence program testing service (ai-pts) model. J. Phys. Conf. Ser. 1228(1), 12017–12017 (2019)
Fernández-Vigo, J., Fernández-Vigo, J.I., Kudsieh, B.: Artificial intelligence, robotics and cyborgs: the future of research and technological development in ophthalmology. Archivos de la Sociedad Española de Oftalmología (English Edition) 94(7), 313–315 (2019)
Raknys, A.V., Gudelis, D., Guogis, A.: The analysis of opportunities of the application of big data and artificial intelligence technologies in public governance and social policy. Socialinė Teorija Empirija Politika ir Praktika 22(6), 88–100 (2021)
Chen, J., Lin, C., Peng, D., et al.: Fault diagnosis of rotating machinery: a review and bibliometric analysis. IEEE Access PP(99),1–1 (2020)
Batarseh, F.A., Freeman, L., Huang, C.H.: A survey on artificial intelligence assurance. J. Big Data 8(1), 1–30 (2021)
Sriram, V.P., Mathur, A., Aarthy, C.J., et al.: Model based using artificial intelligence to overcome the human resource problem in the healthcare industry. Ann. Rom. Soc. Cell Biol. 25(4), 3980–3992 (2021)
Al-Fattah, S.M.: Artificial intelligence approach for modeling and forecasting oil-price volatility. SPE Reservoir Eval. Eng. 22(3), 817–826 (2019)
Wassan, S., Gulati, K., Pallathadka, H., et al.: How artificial intelligence transforms the experience of employees. Turk. J. Comput. Math. Educ. (TURCOMAT) 12(10), 7116–7135 (2021)
Reim, W., Eriksson, O.: Implementation of artificial intelligence (AI): a roadmap for business model innovation. AI 1(2), 180–191 (2020)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Tang, Z., Sun, X., Luo, Y. (2023). Development Road Map and Planning Mode of Artificial Intelligence Technology Under the Background of Internet Information. In: Li, A., Shi, Y., Xi, L. (eds) 6GN for Future Wireless Networks. 6GN 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 505. Springer, Cham. https://doi.org/10.1007/978-3-031-36014-5_17
Download citation
DOI: https://doi.org/10.1007/978-3-031-36014-5_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-36013-8
Online ISBN: 978-3-031-36014-5
eBook Packages: Computer ScienceComputer Science (R0)