Research and Analysis on the Interaction between Queuing Theory and Artificial Intelligence

DOI

10.2991/978-94-6463-300-9_40How to use a DOI?

Keywords

Queuing theory; Artificial intelligence; Simulation; Artificial neural networks; Virtual bookstore; E-Commerce

Abstract

This paper provides a theoretical exploration of queueing theory and its intersection with the rapidly expanding field of artificial intelligence (AI). In an effort to employ AI methodologies in addressing queueing theory problems, an innovative approach is proposed that blends simulation techniques with artificial neural networks (ANNs). This marriage not only exhibits high effectiveness but also holds promise for considerable advancements in applying machine learning methods to queueing theory dilemmas. Beyond theoretical underpinnings, the paper also illuminates practical applications of queueing theory within AI’s domain. It showcases examples from real-life scenarios, such as online bookstores and e-commerce platforms, to demonstrate the strategic deployment of various queueing models to enhance user experiences and system efficiencies. Discussions delve into the advantages of resource allocation, load balancing, and service time optimization, among others. Furthermore, the paper speculates about the evolving relationship between queueing theory and AI, anticipating a future where this connection becomes even more profound and impactful. As AI research continues to advance, novel insights into complex queueing issues and innovative solutions for managing queues in an array of real-world scenarios are expected. This analysis emphasizes the potential richness of integrating queueing theory with AI, paving the way for exciting prospects for future research and applications.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yuanhe Liu
AU  - Ruiming Quan
PY  - 2023
DA  - 2023/11/27
TI  - Research and Analysis on the Interaction between Queuing Theory and Artificial Intelligence
BT  - Proceedings of the 2023 International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2023)
PB  - Atlantis Press
SP  - 391
EP  - 401
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-300-9_40
DO  - 10.2991/978-94-6463-300-9_40
ID  - Liu2023
ER  -