This repository contains the code for the reproducibility of the experiments presented in the dissertation "Research on Deep Learning Model for Seepage Safety Monitoring of Clay-core Wall Dams". Authors: Pan Liao, Xiaoqing Li
We provide a requirements list with all the project dependencies in requirements.txt
.
The config/
directory stores all the configuration files used to run the experiment. config/
stores model configurations used for experiments on imputation.
The scripts used for the experiment in the paper are in the run_experiment.py
and run_inference.py
.
-
run_experiment.py
is used to compute the metrics for the deep pore water pressure prediction methods. An example of usage for GAT-TCN model ispython run_experiment.py --config gat_tcn.yaml --model-name gat_tcn --dataset-name grin
-
run_inference.py
is used for the experiments on sparse datasets using pre-trained models. An example of usage ispython run_inference.py --config inference.yaml --model-name gat_tcn --dataset-name grin --exp-name 20230509T123018_21380673