Artificial Neural Network to Determine Dynamic Effect in Capillary Pressure Relationship for Two-Phase Flow in Porous Media with Micro-Heterogeneities
- Submitting institution
-
De Montfort University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 11232
- Type
- D - Journal article
- DOI
-
10.1007/s40710-014-0045-3
- Title of journal
- Environmental Processes
- Article number
- -
- First page
- 1
- Volume
- 2
- Issue
- 1
- ISSN
- 2198-7491
- Open access status
- Out of scope for open access requirements
- Month of publication
- -
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- 16
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This interdisciplinary research paper was acknowledged for demonstrating the successful application of Artificial Neural Networks for complex environmental modelling such as finding the dynamic coefficient in porous media by Heddam. S., et. al. 2016. The collaboration in the paper has lead on to collaboration on successful grant applications including the recently awarded EPSRC discipline Hopping Grant to Dr Diganta Das on membrane-Cyber Physical System.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
