Using statistical and artificial neural networks to predict the permeability of loosely packed granular materials

Mahdi, FM orcid.org/0000-0002-3046-4389 and Holdich, RG (2017) Using statistical and artificial neural networks to predict the permeability of loosely packed granular materials. Separation Science and Technology, 52 (1). pp. 1-12. ISSN 0149-6395

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Copyright, Publisher and Additional Information: © 2017 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Separation Science and Technology on 20 Sep 2016, available online: https://doi.org/10.1080/01496395.2016.1232735. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: Loosely-packed granular materials, multivariate regression, artificial neural network and permeability prediction
Dates:
  • Published: 2 January 2017
  • Accepted: 1 September 2016
  • Published (online): 20 September 2016
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering (Leeds) > School of Chemical & Process Engineering (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 29 Sep 2017 08:36
Last Modified: 15 Jan 2018 17:54
Status: Published
Publisher: Taylor & Francis
Identification Number: https://doi.org/10.1080/01496395.2016.1232735

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