# TrafficFlowPrediction-1

**Repository Path**: mirick/TrafficFlowPrediction-1

## Basic Information

- **Project Name**: TrafficFlowPrediction-1
- **Description**: 城市交通道路流量预测
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 5
- **Forks**: 1
- **Created**: 2021-02-15
- **Last Updated**: 2024-10-16

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Traffic Flow Prediction
Traffic Flow Prediction with Neural Networks(SAEs、LSTM、GRU).

## Requirement
- Python 3.6    
- Tensorflow-gpu 1.5.0  
- Keras 2.1.3
- scikit-learn 0.19

## Train the model

**Run command below to train the model:**

```
python train.py --model model_name
```

You can choose "lstm", "gru" or "saes" as arguments. The ```.h5``` weight file was saved at model folder.


## Experiment

Data are obtained from the Caltrans Performance Measurement System (PeMS). Data are collected in real-time from individual detectors spanning the freeway system across all major metropolitan areas of the State of California.
	

**Run command below to run the program:**


```
python main.py
nihao

```