ShuaiGuo16/Multi-Fidelity-ML
Project source code and data for multi-fidelity machine learning strategy for flame model identification
This project helps combustion engineers and researchers accurately identify flame models from noisy time-series data to improve combustor design and analysis. It takes in experimental or simulation data from flame tests and provides a more accurate and robust flame model. This is for professionals involved in combustion engineering, especially those designing or analyzing gas turbines and industrial burners.
No commits in the last 6 months.
Use this if you need to accurately identify flame frequency response (FTF) models from experimental or simulated data, especially when dealing with noisy measurements or limited computational resources.
Not ideal if your work does not involve combustion systems or if you primarily need general-purpose machine learning model development not specific to flame model identification.
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1
Language
MATLAB
License
—
Category
Last pushed
Feb 02, 2021
Commits (30d)
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