Building Modelling using GNN

gcn2.py

uses GNN-RNN architecture and was able to achieve on par performance to a typical mlp (RNN) based model
gcn2 uses a GCN for generating a representation of the graph nodes, and the nodes are passed into a RNN layer

data_collect.py: collects system-excited (randomly set actuation value) -> the data is not in graph format
data_scale.py: data dimension goes over the scikitlearn.StandardScaler capability
data_process.py: loop over the collected data, embed the vector data in graph format
gcn2.py: include PyG dataloader + model + training code

Name		Name	Last commit message	Last commit date
Latest commit History 17 Commits
.auctex-auto		.auctex-auto
old		old
utils		utils
.gitignore		.gitignore
GHTIn.idf		GHTIn.idf
README.md		README.md
base_data_collect.py		base_data_collect.py
data_collect.py		data_collect.py
data_process.py		data_process.py
data_scale.py		data_scale.py
gcn2.py		gcn2.py
gnn.pdf		gnn.pdf
gnn.synctex.gz		gnn.synctex.gz
gnn.tex		gnn.tex
in.idf		in.idf
lp.py		lp.py
weather.epw		weather.epw