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Traffic Flow Prediction with Improved SOPIO-SVR Algorithm

机译：改进SOPIO-SVR算法的交通流量预测

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摘要

In urban public transport, the traffic flow prediction is a classical non-linear complicated optimization problem, which is very important for public transport system. With the rapid development of the big data, Smart card data of bus which is provided by millions of passengers traveling by bus across several days plays a more and more important role in our daily life. The issue that we address is whether the data mining algorithm and the intelligent optimization algorithm can be applied to forecast the traffic flow from big data of bus. In this paper, a novel algorithm which called mixed support vector regression with sub-space orthogonal pigeon-Inspired Optimization (SOPIO-MSVR) is used to predict the traffic flow and optimize the algorithm progress. Results show the SOPIO-MSVR algorithm outperforms other algorithms by a margin and is a competitive algorithm. And the research can make the significant contribution to the improvement of the transportation.
机译：在城市公共交通中，交通流量预测是一个经典的非线性复杂优化问题，对于公共交通系统非常重要。随着大数据的快速发展，数百万乘公交车的乘客在几天内提供的公交车智能卡数据在我们的日常生活中发挥着越来越重要的作用。我们要解决的问题是，是否可以将数据挖掘算法和智能优化算法用于从公交大数据中预测交通流量。本文提出了一种新的算法，即混合支持向量回归与子空间正交鸽子启发优化算法（SOPIO-MSVR），用于预测交通流量并优化算法进度。结果表明，SOPIO-MSVR算法比其他算法略胜一筹，是一种竞争算法。研究可以为交通运输的改善做出重要的贡献。

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  • 来源
  • 会议地点 Beijing(CN)
  • 作者

    Xuejun Cheng; Lei Ren; Jin Cui; Zhiqiang Zhang;

  • 作者单位

    School of Automation Science and Electrical Engineering, Beihang University, Beijing, China,Engineering Research Center of Complex Product Advanced Manufacturing System, Ministry of Education, Beijing, China;

    School of Automation Science and Electrical Engineering, Beihang University, Beijing, China,Engineering Research Center of Complex Product Advanced Manufacturing System, Ministry of Education, Beijing, China;

    School of Automation Science and Electrical Engineering, Beihang University, Beijing, China,Engineering Research Center of Complex Product Advanced Manufacturing System, Ministry of Education, Beijing, China;

    School of Automation Science and Electrical Engineering, Beihang University, Beijing, China,Engineering Research Center of Complex Product Advanced Manufacturing System, Ministry of Education, Beijing, China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Traffic flow prediction; SOPIO-MSVR; Classification model;

    机译：交通流量预测； SOPIO-MSVR;分类模型;

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