Research on the Ideological and Political System of Logistics System Simulation Course in the Context of Artificial Intelligence
- DOI
- 10.2991/978-94-6463-242-2_64How to use a DOI?
- Keywords
- Artificial Intelligence; Logistics System Simulation; Ideological and political education; Partial Particle Swarm Optimization Algorithm
- Abstract
Universities are trying to integrate algorithms into the teaching of logistics system simulation courses. However, students have difficulty in understanding algorithms due to the complex teaching formulas and computational processes. The main purpose of this paper is to solve the current teaching dilemma of algorithms. Taking the representative partial example group algorithm of optimization algorithm as an example, introducing the detailed steps and modeling process of the partial example group algorithm. Based on this, the algorithm is applied to the actual logistics system simulation modeling, and the computer is used with classroom teaching to help students understand the algorithm quickly. This paper shows that the use of algorithms can largely improve the efficiency and optimize the results of logistics system simulation, and provides a paradigm for teaching similar undergraduate teaching contents and knowledge points.
- Copyright
- © 2024 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.
Cite this article
TY - CONF AU - Yan Tang AU - Anqi Cui AU - Yang Hu PY - 2023 DA - 2023/09/22 TI - Research on the Ideological and Political System of Logistics System Simulation Course in the Context of Artificial Intelligence BT - Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023) PB - Atlantis Press SP - 519 EP - 525 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-242-2_64 DO - 10.2991/978-94-6463-242-2_64 ID - Tang2023 ER -