基于边缘智能的国际内陆港口快速自适应传输模型研究

IF 3.7 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS
Yiwen Liu, Zhirong Zhu, Tangyan, Wenkan Wen, Xiaoning Peng, Yuanquan Shi
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引用次数: 0

摘要

本文提出了一种基于智能边缘调度的物流国际内陆港资源配置方法,通过在城市系统中构建边缘网络,对物流资源进行合理的预分配。采用多个综合学习模型和区域流行度分类算法,预测各子分布点的分布需求。该方法能够处理配送量大、配送情况多变、运输距离长等不确定性问题。以怀化国际内河港为仿真对象,仿真结果表明,该方法具有最高的物流配送效率,且在紧急情况下仍具有较高的适应性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Fast Adaptive Transmission Models for International Inland Port Based on Edge Intelligence
In this paper, we propose a logistics International Inland Port resource allocation method based on intelligent edge scheduling, and we do a reasonable pre-allocation of logistics resources by building an edge network in the urban system. By using multiple integrated learning models and regional prevalence classification algorithms, the distribution demand of each sub-distribution point is predicted. The proposed method is able to cope with uncertainties such as high distribution volume, variable distribution situations or long transportation distances. We use the HuaiHua International Inland Port as the simulation object, and the simulation results show that the proposed method has the highest efficiency in logistics distribution and is still highly adaptive in emergency situations.
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来源期刊
Journal of Cloud Computing-Advances Systems and Applications
Journal of Cloud Computing-Advances Systems and Applications Computer Science-Computer Networks and Communications
CiteScore
6.80
自引率
7.50%
发文量
76
审稿时长
75 days
期刊介绍: The Journal of Cloud Computing: Advances, Systems and Applications (JoCCASA) will publish research articles on all aspects of Cloud Computing. Principally, articles will address topics that are core to Cloud Computing, focusing on the Cloud applications, the Cloud systems, and the advances that will lead to the Clouds of the future. Comprehensive review and survey articles that offer up new insights, and lay the foundations for further exploratory and experimental work, are also relevant.
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