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论文 Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction代码重构

本代码使用Tensorflow 1.5 重构自项目:https://github.com/lucktroy/DeepST

博客:https://blog.csdn.net/The_lastest/article/details/85001601

更新记录

2020-01-01

  • 在主页增加使用说明

2019-07-06

  • 修复数据预处理中reshape与``transpose`误用的错误

2018-12-14

  • 完成了整个框架的搭建和调试工作;
  • 完成了一次完整的训练和结果记录;

使用指南

  • 1.安装

    安装好tensorflow-gpu 1.5.0版本,下载好数据集解压后放到data/TaxiBJ/目录下即可;

    下载页面:

    • BJ16_M32x32_T30_InOut.h5
    • BJ15_M32x32_T30_InOut.h5
    • BJ14_M32x32_T30_InOut.h5
    • BJ13_M32x32_T30_InOut.h5
    • BJ_Meteorology.h5
    • BJ_Holiday.txt

    将下载好的这六个文件放到data/TaxiBJ/目录

  • 2.训练

    下载完成数据后进入TaxiBJ文件夹,在``exptTaxiBJ.py中设置好相关参数,运行 python exptTaxiBJ.py`即可开始训练;

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