This is a PyTorch implementation of our work Developing a Long Short-Term Memory (LSTM) based Model for Predicting Water Table Depth in Agricultural Areas.[Paper]
Python3.x
pytorch>=0.4.0
numpy>=1.14.0
pandas>=0.22.0
scikit-learn>=0.14
The code was tested with Python 3.5. To use this code, please do:
-
Clone the repo:
git clone https://github.com/jfzhang95/Water-Table-Depth-Prediction-PyTorch cd Water-Table-Depth-Prediction-PyTorch -
Install dependencies:
pip install matplotlib numpy pandas scikit-learn
For pytorch installation, please see in PyTorch.org.
- To try the demo code, please run:
python demo.py
If installed correctly, the result should look like this:
Noted that the demo data (demo.csv) are processed manually, so they are not real data, but they still can reflect the correlation between the original data.
If you use this code, please consider citing our paper:
@article{zjf18,
journal = {Journal of Hydrology},
title = {Developing a Long Short-Term Memory (LSTM) based Model for Predicting Water Table Depth in Agricultural Areas},
author = {Jianfeng Zhang, Yan Zhu, Xiaoping Zhang, Ming Ye and Jinzhong Yang},
year = {2018},
volume = {561},
pages = {918-929}
}