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Development of Transport Mode Choice Model with Neural Network

机译:用神经网络开发运输方式选择模型

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摘要

Mode choice is a key decision in trip making process. Traditionally mode choice analysis is based on mathematical modeling framework like Logit or Probit models. Despite limitations, such models are widely used by transport planners for their computational ease and theoretical transparency. But the major problems with such models are the lack of flexibility and rigidity regarding specification 'Neural Network' technique has the capability to overcome these limitations. Also due to its affinity to natural learning and decision-making process it has become a highly popular tool for analysis. This paper describes the development of a transport mode choice model based on neural network technique using MATLAB. The paper also presents comparison between two different architectures of the model, along with the scope of real time application of the model.
机译:模式选择是旅行过程中的关键决定。传统上,模式选择分析基于数学建模框架,例如Logit或Probit模型。尽管有局限性,但此类模型因其计算简便和理论透明性而被运输计划人员广泛使用。但是,此类模型的主要问题是缺乏灵活性和刚性,因为规范“神经网络”技术无法克服这些限制。同样,由于它对自然学习和决策过程的亲和力,它已成为非常流行的分析工具。本文描述了使用MATLAB基于神经网络技术的运输模式选择模型的开发。本文还介绍了模型的两种不同体系结构之间的比较,以及模型的实时应用范围。

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