Development of a Supervised Learning Model to Predict Length Scale Dependent Permeability of Porous Carbon Composites
Author:
Funder
National Aeronautics and Space Administration
Publisher
Springer Science and Business Media LLC
Subject
General Chemical Engineering,Catalysis
Link
https://link.springer.com/content/pdf/10.1007/s11242-023-02004-5.pdf
Reference37 articles.
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2. Bastian, P., Kraus, J., Scheichl, R., Wheeler, M.: Simulation of Flow in Porous Media: Applications in Energy and Environment, vol. 12. De Gruyter, Boston (2013). https://doi.org/10.1515/9783110282245
3. Battiti, R., Masulli, F.: Bfgs optimization for faster and automated supervised learning. International Neural Network Conference 2(1), 757–760 (1990). https://doi.org/10.1007/978-94-009-0643-3_68
4. Bear, J.: Dynamics of Fluids in Porous Media, vol. 1. Courier Corporation, Chelmsford (1988). https://doi.org/10.1097/00010694-197508000-00022
5. Belousov, A.I., Verzakov, S.A., Frese, J.V.: A flexible classification approach with optimal generalisation performance: support vector machines. Chemom. Intell. Lab. Syst. 64(1), 15–25 (2002). https://doi.org/10.1016/S0169-7439(02)00046-1
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