供应链中最常见的中断类型——基于人工神经网络方法的评估

IF 1.4 4区 工程技术 Q3 MANAGEMENT
A. Lorenc, Małgorzata Kuźnar
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引用次数: 7

摘要

这篇文章的重点是多式联运。文章中使用了开发的方法来估计供应链中最常见的中断类型,即道路运输过程中的货物盗窃,从而估计出现盗窃风险的概率,但文章中提出的方法可用于估计供应链其他类型中断出现的概率。本文概述了一种使用人工神经网络识别和预测供应链中断的复杂方法。该方法基于供应链中断的最新数据,允许对供应链中断做出适当反应,以最大限度地减少损失和与损失相关的成本。开发的模型可用于支持关于高盗窃风险运输案件的额外货物保险的决策,或使用货物位置或参数的监控系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The most common type of disruption in the supply chain - evaluation based on the method using artificial neural networks
The article focuses on intermodal transport. Developed method was used in article to estimate the most common type of disruptions in supply chain, which turned out to be a cargo theft during road transport, and hence the probability of theft risk appearance, but presented in the article method can be useful to estimate the probability of appearance other types of disruptions in the supply chain. The article presents an outline of a complex method uses ANN for identifying and forecasting disruptions in the supply chain. This method is based on the latest data of disruptions in the supply chain, which allow for appropriate response to supply chain disruptions in order to minimise losses and costs associated with losses. Developed model can be used to support decisions about additional cargo insurance for high risk of theft transport cases or the usage of monitoring systems for the location or parameters of the cargo.
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来源期刊
CiteScore
2.10
自引率
13.30%
发文量
35
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