Mass Calibration of Soft Sensors Using Optimal Transportation and Neural Network

This is the source code of the paper "Adaptive Calibration of Soft Sensors using Optimal Transportation Transfer Learning for Mass Production and Long-Term Usage," published in Advanced Intelligent Systems.

Python file "Soft Sensor Mass Calibration.py" demonstrates how domain adaptation is implemented in the mass calibration situation. Excel file "Mass_total" is a sample data (about 10% of total size) obtained from our experiments.

If this source information is of your interest, please refer to our full paper; this paper is open-access to all users.

Paper URL: https://onlinelibrary.wiley.com/doi/full/10.1002/aisy.201900178

Paper DOI: https://doi.org/10.1002/aisy.201900178

Contact shigumchis(at)snu(dot)ac(dot)kr if you have any questions.

Environments

Python 2.7 Tensorflow 1.3.0

Citation

Please cite our work as follows:

@article{kim2020transfer,
  title={Adaptive Calibration of Soft Sensors Using Optimal Transportation Transfer Learning for Mass Production and Long‐Term Usage},
  author={Kim, DongWook and Kwon, Junghan and Jeon, Byung Jun and Park, Yong-Lae},
  journal={Advanced Intelligent Systems},
  pages={1900178},
  publisher={Wiley Online Library},
  year={2020},
  doi={10.1002/aisy.201900178},
  url={https://doi.org/10.1002/aisy.201900178}
}