Enhancing Logistics Efficiency through Computer and Network Technologies: A Pathway to Industry Informatization

Jennifer Glick

doi:10.54097/e05gkp44

Authors

Jennifer Glick

DOI:

https://doi.org/10.54097/e05gkp44

Keywords:

Computer technology; logistics industry; informatization; application.

Abstract

The rapid development of computer and network technology provides a solid foundation for the informatization of logistics industry. Through INTERNET, logistics branches, suppliers, customers, etc. scattered in different geographical locations are connected to form an information network for information transmission and sharing, so that all parties can understand the operation of businesses in different places in real time and improve the operation efficiency of logistics activities. Based on the broad prospects of computers in the logistics industry, this paper conducts in-depth research on logistics modernization and logistics informatization, the impact of computer technology on the logistics industry, and the countermeasures to accelerate logistics industry informatization.

Downloads

Download data is not yet available.

References

Liang, Y., Wang, X., Wu, Y. C., Fu, H., & Zhou, M. (2023). A Study on Blockchain Sandwich Attack Strategies Based on Mechanism Design Game Theory. Electronics, 12(21), 4417.

Li, X., Wang, X., Chen, X., Lu, Y., Fu, H., & Wu, Y. C. (2024). Unlabeled data selection for active learning in image classification. Scientific Reports, 14(1), 424.

Guo, H., Ma, Z., Chen, X., Wang, X., Xu, J., & Zheng, Y. (2024). Generating Artistic Portraits from Face Photos with Feature Disentanglement and Reconstruction. Electronics, 13(5), 955.

Lee, Z., Wu, Y. C., & Wang, X. (2023, October). Automated Machine Learning in Waste Classification: A Revolutionary Approach to Efficiency and Accuracy. In Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition (pp. 299-303).

El Naqa, I., & Murphy, M. J. (2015). What is machine learning? (pp. 3-11). Springer International Publishing.

Sammut, C., & Webb, G. I. (Eds.). (2011). Encyclopedia of machine learning. Springer Science & Business Media.

Woschank, M., Rauch, E., & Zsifkovits, H. (2020). A review of further directions for artificial intelligence, machine learning, and deep learning in smart logistics. Sustainability, 12(9), 3760.

Tsolaki, K., Vafeiadis, T., Nizamis, A., Ioannidis, D., & Tzovaras, D. (2022). Utilizing machine learning on freight transportation and logistics applications: A review. ICT Express.

Singh, A., Wiktorsson, M., & Hauge, J. B. (2021). Trends in machine learning to solve problems in logistics. Procedia CIRP, 103, 67-72.

Zhang Yi. Analysis on Multiple Levels and Optimization Methods of Modern Logistics Information System [J]. Business Culture (the second half of the month), 2012, 9:19-20