Sustainability ranking of desalination plants using mamdani fuzzy logic inference systems
(2020) In Sustainability (Switzerland) 12(2).- Abstract
As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems.... (More)
As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability.
(Less)
- author
- Rustum, Rabee ; Kurichiyanil, Anu Mary John ; Forrest, Shaun ; Sommariva, Corrado ; Adeloye, Adebayo J. ; Zounemat-Kermani, Mohammad and Scholz, Miklas LU
- organization
- publishing date
- 2020
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Artificial intelligence, Decision-making in water supply, Energy efficiency, Ranking modelling framework, Reverse osmosis, Sustainability indicator list, Sustainability tool, Sustainable water production, Unsustainable production, Water pollution
- in
- Sustainability (Switzerland)
- volume
- 12
- issue
- 2
- article number
- 631
- publisher
- MDPI AG
- external identifiers
-
- scopus:85079759534
- ISSN
- 2071-1050
- DOI
- 10.3390/su12020631
- language
- English
- LU publication?
- yes
- id
- ecf74e33-478a-40a8-9fdc-0f43807962de
- date added to LUP
- 2020-03-19 06:56:15
- date last changed
- 2022-04-18 21:08:32
@article{ecf74e33-478a-40a8-9fdc-0f43807962de,
abstract = {{<p>As water desalination continues to expand globally, desalination plants are continually under pressure to meet the requirements of sustainable development. However, the majority of desalination sustainability research has focused on new desalination projects, with limited research on sustainability performance of existing desalination plants. This is particularly important while considering countries with limited resources for freshwater such as the United Arab Emirates (UAE) as it is heavily reliant on existing desalination infrastructure. In this regard, the current research deals with the sustainability analysis of desalination processes using a generic sustainability ranking framework based on Mamdani Fuzzy Logic Inference Systems. The fuzzy-based models were validated using data from two typical desalination plants in the UAE. The promising results obtained from the fuzzy ranking framework suggest this more in-depth sustainability analysis should be beneficial due to its flexibility and adaptability in meeting the requirements of desalination sustainability.</p>}},
author = {{Rustum, Rabee and Kurichiyanil, Anu Mary John and Forrest, Shaun and Sommariva, Corrado and Adeloye, Adebayo J. and Zounemat-Kermani, Mohammad and Scholz, Miklas}},
issn = {{2071-1050}},
keywords = {{Artificial intelligence; Decision-making in water supply; Energy efficiency; Ranking modelling framework; Reverse osmosis; Sustainability indicator list; Sustainability tool; Sustainable water production; Unsustainable production; Water pollution}},
language = {{eng}},
number = {{2}},
publisher = {{MDPI AG}},
series = {{Sustainability (Switzerland)}},
title = {{Sustainability ranking of desalination plants using mamdani fuzzy logic inference systems}},
url = {{http://dx.doi.org/10.3390/su12020631}},
doi = {{10.3390/su12020631}},
volume = {{12}},
year = {{2020}},
}