Predicting combined sewer overflows chamber depth using artificial neural networks with rainfall radar data

Mounce, S.R., Shepherd, W., Sailor, G. et al. (2 more authors) (2014) Predicting combined sewer overflows chamber depth using artificial neural networks with rainfall radar data. Water Science and Technology, 69 (6). 1326 - 1333. ISSN 0273-1223

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Authors/Creators:
  • Mounce, S.R.
  • Shepherd, W.
  • Sailor, G.
  • Shucksmith, J.
  • Saul, A.J.
Copyright, Publisher and Additional Information: © 2014 IWA Publishing. This is an author produced version of a paper subsequently published in Water Science & Technology. Uploaded in accordance with the publisher's self-archiving policy.
Keywords: artificial neural networks; combined sewer overflows; cross correlation; depth monitoring; prediction; rainfall radar
Dates:
  • Published: 21 January 2014
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 25 Mar 2015 09:25
Last Modified: 21 Mar 2018 12:18
Published Version: http://dx.doi.org/10.2166/wst.2014.024
Status: Published
Publisher: IWA Publishing
Identification Number: https://doi.org/10.2166/wst.2014.024

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