# Origin-Destination prediction from Road Segment Average Speed Data using GraphResLSTM Model

# torch version: 1.12.1+cu116

# torch_geometric version: 2.1.0.post1

# numpy version: 1.23.3

# pandas version: 1.4.2

# matplotlib version: 3.5.1

## 0. Data .npy usage

### Load the array from the.npy file using numpy.load

`import numpy as np` 

`loaded_array = np.load('example_array.npy')`
`print(loaded_array) `

## 1.CNN.py is a comparative algorithm applying the CNN Algorithm for OD Prediction.

## 2.GCN.py is a comparative algorithm applying the GCN Algorithm for OD Prediction.

## 3.LSTM.py is a comparative algorithm applying the LSTM Algorithm for OD Prediction.

## 4.CNN_LSTM.py is a comparative algorithm applying the CNN AND LSTM Algorithm for OD Prediction.

## 5.GCN_LSTM.py is a comparative algorithm applying the GCN AND LSTM Algorithm for OD Prediction.

## 6.GraphResLSTM.py is a algorithm applying the GCN AND RESNET AND LSTM Algorithm for OD Prediction.

## 7. func_Data_Input.py serves to delineate the procedures for data ingestion and model training.

## 8. func_Loss serves to describe the loss function.

## 9. traci traci code for generate data.py is the traci code for generate data.