Deep learning for gas sensing using MOFs coated weakly-coupled microbeams

DOI10.1016/J.APM.2022.01.008zbMath1505.74160OpenAlexW4207021896MaRDI QIDQ2109926

Vladimir Evgenievich Puzyrev, Rana Sabouni, Mehdi Ghommem, Fehmi Najar

Publication date: 21 December 2022

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.apm.2022.01.008

zbMATH Keywords

nonlinear dynamicsdeep learningMOFMEMS gas sensorweakly-coupled microbeams

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Control, switches and devices (``smart materials) in solid mechanics (74M05)

Uses Software

• Adam

Cites Work

• Fluid sensing using microcantilevers: from physics-based modeling to deep learning
• Deep learning for simultaneous measurements of pressure and temperature using arch resonators
• Practical selection of SVM parameters and noise estimation for SVM regression
• Strong nonlinear dynamics of MEMS and NEMS structures based on semi-analytical approaches
• An energy approach to the solution of partial differential equations in computational mechanics via machine learning: concepts, implementation and applications
• A Concordance Correlation Coefficient to Evaluate Reproducibility

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