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华为杯2021数学建模B题

主要包含两个部分, 一部分是B题中用到的部分计算程序:problems

另一部分是深度学习模型例如rnn, lstm用到的训练程序: multivariate_time_series_rnn, 现在对程序结构比较复杂的多元时间序列rnn 程序进行简单介绍

1. multivariate_time_series_rnn 介绍

我们用了两个深度学习模型rnn和lstm,

  • ./multivariate_time_series_rnn/networks

模型构造文件,包含用到的rnn和lstm

  • ./multivariate_time_series_rnn/opts/*.yaml

文件来训练的过程的设置, 例如训练轮数, 模型选择等.

  • ./multivariate_time_series_rnn/dataset

放置了给定的气象&污染物表格数据的载入程序, 能够灵活调整数据形式,有监督训练模型

  • ./multivariate_time_series_rnn/scripts

可执行python文件

  • ./multivariate_time_series_rnn/splits

数据集索引

2. multivariate_time_series_rnn 应用

note:首先通过 ./problems下数据预处理程序将数据集整理好
  • 实验平台重要的依赖项
pytorch 1.5.1
cuda 10.1
tensorboardX
  • 训练

编辑 opts/*.yaml文件然后 python scripts/train.py。 如果设置正确, 终端如下所示

训练终端情况

  • 可视化过程

跟踪到 *.yaml文件里的log_dir然后

tensorboard --logdir=.

浏览器打开127.0.0.1:6006观看训练时损失函数变化以及模型的绝对误差AbsRel曲线变化,如下图所示

tensorboard

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