Theory-guided hard constraint projection (HCP): a knowledge-based data-driven scientific machine learning method

Thank you for your interest in our work. For more details, please refer to the paper Theory-guided hard constraint projection (HCP).

The detailed introduction video (in Chinese) about HCP can be found in the following link: https://jmq.h5.xeknow.com/s/4mS6b1

The ppt of the HCP can be downloaded at: https://pan.baidu.com/s/1-yHLqIX38x4x6gbWmugm8A password is: b54e

Citation information: Chen, Y., Huang, D., Zhang, D., Zeng, J., Wang, N., Zhang, H., & Yan, J. (2021). Theory-guided hard constraint projection (HCP): a knowledge-based data-driven scientific machine learning method. Journal of Computational Physics, 110624.

The code structure is shown in the illustration.

Researchers can modify the experiment setting through the configure.py file. This code can implement HCP, TgNN and conventional ANN respectively for comparative experiments.

If you have any questions, please feel free to contact me. E-mail: [email protected]

Citation: Chen, Y., Huang, D., Zhang, D., Zeng, J., Wang, N., Zhang, H., & Yan, J. (2021). Theory-guided hard constraint projection (HCP): A knowledge-based data-driven scientific machine learning method. Journal of Computational Physics, 445, 110624.