Performance Prediction of the Full-Scale Bardenpho Advanced Sewage Treatment Process Using a Genetic Adapted Time-Delay Neural Network (GATDNN)
- Submitting institution
-
London South Bank University
- Unit of assessment
- 13 - Architecture, Built Environment and Planning
- Output identifier
- 290517
- Type
- D - Journal article
- DOI
-
10.33768/ksue.2018.18.3.279
- Title of journal
- Journal of the Korean Society of Urban Environment
- Article number
- -
- First page
- 279
- Volume
- 18
- Issue
- 3
- ISSN
- 1598-253X
- Open access status
- Other exception
- Month of publication
- September
- Year of publication
- 2018
- URL
-
https://www.earticle.net/Article/A348227
- Supplementary information
-
-
- Request cross-referral to
- 12 - Engineering
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
1
- Research group(s)
-
A - Centre for Civil and Buildings Services Engineering
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- -
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
