Testing Occam's razor to characterize high-order connectivity in pore networks of granular media: Feature selection in machine learning

J Van Der Linden; A Tordesillas; G Narsilio

Conference Proceedings

Testing Occam's razor to characterize high-order connectivity in pore networks of granular media: Feature selection in machine learning

J Van Der Linden, A Tordesillas, G Narsilio, F Radjai (ed.), S Nezamabadi (ed.), S Luding (ed.), JY Delenne (ed.)

EPJ Web of Conferences | EDP Sciences | Published : 2017

DOI: 10.1051/epjconf/201714012006

Abstract

© The Authors, published by EDP Sciences, 2017. A perennial challenge for the characterization and modelling of phenomena involving granular media is that the internal connectivity of, and interactions between, the pores and the particles exhibit hallmarks of complexity: multi-scale and nonlinear interactions that lead to a plethora of patterns at the mesoscale, including fluid flow patterns that ultimately render a permeability of the granular media at the macroscale. A multitude of physical parameters exist to characterize geometry and structure, including pore/particle shape, volume and surface area, while a rich class of complex network parameters quantifies internal connectivity of the ..

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University of Melbourne Researchers

Antoinette Tordesillas Author

Guillermo Narsilio Ferrero Author

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Awarded by Air Force Office of Scientific Research

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Keywords

51 Physical Sciences

5107 Particle and High Energy Physics

Machine Learning and Artificial Intelligence

5110 Synchrotrons and Accelerators

Networking and Information Technology R&d (nitrd)