Using artificial neural networks for transport decisions : managerial guidelines

R. Cook, L. Jenicke, B. Gibson
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Abstract

One information technology that may be considered by transportation managers, and which is included in the portfolio of technologies that encompass TMS. is artificial neural networks (ANNs). These artificially intelligent computer decision support software provide solutions by finding and recognizing complex patterns in data. ANNs have been used successfully by transportation managers to forecast transportation demand, estimate future transport costs, schedule vehicles and shipments, route vehicles and classify earners for selection. Artificial neural networks excel in transportation decision environments that are dynamic, complex and unstructured. This article introduces ANNs to transport managers by describing ANN technological capabilities, reporting the current status of transportation neural network applications, presenting ANN applications that offer significant potential for future development and offering managerial guidelines for ANN development.
使用人工神经网络进行运输决策:管理指南
运输管理人员可能考虑的一种信息技术,它包含在包含TMS的技术组合中。是人工神经网络(ann)。这些人工智能计算机决策支持软件通过发现和识别数据中的复杂模式来提供解决方案。交通管理人员已经成功地使用人工神经网络来预测运输需求,估计未来的运输成本,安排车辆和运输,车辆路线和分类选择。人工神经网络在动态、复杂和非结构化的交通决策环境中表现优异。本文通过描述人工神经网络的技术能力,报告运输神经网络应用的现状,介绍具有未来发展潜力的人工神经网络应用,并为人工神经网络的发展提供管理指南,向运输管理人员介绍人工神经网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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