Skip to main content

Physics-Informed Modularized Neural Network for Building Energy Modeling

Project description

ModNN

ModNN is a Modularized Physics-Informed Neural Network for building energy modeling.

It incorporates with physics-informed model structure, loss function, and model constraints.


🚀 Installation

You can install the package using pip:

pip install modnn

🧠 Example

Please find the online Jupyter notebook for a step-by-step instruction: https://colab.research.google.com/drive/1A2jt1q53RtxGuaoym6N1PmlKELDPpYFX?usp=sharing

🧠 Update log

To further improve physics consistency, I replaced heattransfer module by energy balance equations, start from version 2.0.0

🧪 Requirements

Python 3.7+

PyTorch

NumPy

Pandas

Matplotlib

Seaborn

scikit-learn

tqdm

📬 License

MIT License

🙋‍♂️ Author

Zixin Jiang: zjiang19@syr.edu

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

modnn-3.0.0.tar.gz (35.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

modnn-3.0.0-py3-none-any.whl (41.7 kB view details)

Uploaded Python 3

File details

Details for the file modnn-3.0.0.tar.gz.

File metadata

  • Download URL: modnn-3.0.0.tar.gz
  • Upload date:
  • Size: 35.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.0

File hashes

Hashes for modnn-3.0.0.tar.gz
Algorithm Hash digest
SHA256 1b78c5e0ec9bb596e1f7ee11e0662b1cb0c6c76219e0805351b36735fc12f330
MD5 76a8300d842e99a8436e82b704724557
BLAKE2b-256 5bfa03dda6c3667b18c5b546d9bc125962ca7fd8fcbe427cd06219b427abf1dc

See more details on using hashes here.

File details

Details for the file modnn-3.0.0-py3-none-any.whl.

File metadata

  • Download URL: modnn-3.0.0-py3-none-any.whl
  • Upload date:
  • Size: 41.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.0

File hashes

Hashes for modnn-3.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 5918d62af39409684a33c84f05624ccccc8b2753559d59ab88ea2e48fd0f9255
MD5 a99529c3f7b5070ad0edb67685957c33
BLAKE2b-256 bb1f8df3be18966eb26871800952ee46b4db6f7e9b7fe3351b81a2869a85cbf2

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page