Deep Neural Networks for Predicting Vehicle Travel Times

Arthur Cruz de Araujo, A. Etemad
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引用次数: 9

Abstract

This paper focuses on prediction if vehicle travel time. An established open dataset of taxi trips in New York City is used. We first perform statistical analysis on the data in order to determine the informative features that can be used for the problem at hand. Successive to detailed analysis of the data and features, we develop a deep neural network for travel time prediction. We show that our model performs with high accuracy, and outperforms a number of baseline techniques.
预测车辆行驶时间的深度神经网络
本文主要研究车辆行驶时间的预测问题。本文使用了纽约市出租车旅行的开放数据集。我们首先对数据进行统计分析,以确定可用于当前问题的信息特征。在详细分析数据和特征的基础上,提出了一种用于行程时间预测的深度神经网络。我们表明,我们的模型具有很高的准确性,并且优于许多基线技术。
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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