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Statistical methods versus neural networks in transportation research: Differences, similarities and some insights

机译:交通研究中的统计方法与神经网络:差异,相似点和一些见解

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摘要

In the field of transportation, data analysis is probably the most important and widely used research tool available. In the data analysis universe, there are two 'schools of thought'; the first uses statistics as the tool of choice, while the second - one of the many methods from - Computational Intelligence. Although the goal of both approaches is the same, the two have kept each other at arm's length. Researchers frequently fail to communicate and even understand each other's work. In this paper, we discuss differences and similarities between these two approaches, we review relevant literature and attempt to provide a set of insights for selecting the appropriate approach.
机译:在运输领域,数据分析可能是最重要且使用最广泛的研究工具。在数据分析领域中,有两个“思想流派”。第一种使用统计数据作为选择工具,第二种使用计算智能。尽管这两种方法的目标是相同的,但两者保持了一定距离。研究人员经常无法交流甚至无法理解彼此的工作。在本文中,我们讨论了这两种方法之间的差异和相似性,我们回顾了相关文献并试图为选择合适的方法提供一系列见解。

著录项

  • 来源
    《Transportation research》 |2011年第3期|p.387-399|共13页
  • 作者单位

    Department of Transportation Planning and Engineering, School of Civil Engineering, National Technical University of Athens. Athens, Greece;

    Department of Transportation Planning and Engineering, School of Civil Engineering, National Technical University of Athens. Athens, Greece;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    statistical models; neural networks; transportation research;

    机译:统计模型;神经网络;交通运输研究;
  • 入库时间 2022-08-18 01:18:39

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