Skip to content

DarrellDai/LSTM-for-Dynamic-system

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

LSTM-for-Dynamic-system

Comparing 3 types of LSTMs for Dynamic system: Classic LSTM, Multiplicative LSTM (mLSTM) and LSTM with Attention.

Difference metrics are included: MSE, Kullback–Leibler divergence and 2-Wasserstein Distance.

Data is from topographic barotropic model, which can be downloaded from https://drive.google.com/drive/folders/1ceFUYHvZWMh35JWEAhDpjvoK0RK_fKbu?usp=sharing.

run train_model_para.py to train model

run pred_model.py to make prediction

Results are collected in Report.pdf

About

3 types of LSTMs for Dynamic system

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published