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Can machine language and artificial intelligence revolutionize process automation for water treatment and desalination?

Saif Al Aani, Talal Bonny, Shadi W. Hasan, Nidal Hilal

Desalination, Volume: 458, Pages: 84 - 96

Swansea University Author: Nidal Hilal

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DOI (Published version): 10.1016/j.desal.2019.02.005

Abstract

Artificial intelligence (AI) is a powerful tool that is commonly applied in engineering multi-disciplines owing to its functionality to resolve real-world problems where deterministic solutions are arduous to achieve. Revolution in water treatment and desalination process automation has been emergin...

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Published in: Desalination
ISSN: 0011-9164
Published: 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa48789
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first_indexed 2019-02-11T11:58:09Z
last_indexed 2019-03-27T11:20:10Z
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spelling 2019-03-26T13:51:27.7827587 v2 48789 2019-02-11 Can machine language and artificial intelligence revolutionize process automation for water treatment and desalination? 3acba771241d878c8e35ff464aec0342 Nidal Hilal Nidal Hilal true false 2019-02-11 FGSEN Artificial intelligence (AI) is a powerful tool that is commonly applied in engineering multi-disciplines owing to its functionality to resolve real-world problems where deterministic solutions are arduous to achieve. Revolution in water treatment and desalination process automation has been emerging recently. Several challenges are present in the water sector related to data structur-ing and smart water services through which AI would have great potential once those issues are addressed. The distinctive tools of AI, mainly; artificial neural networks (ANNs), as a regression model, and genetic algorithm (GA), as one of the global optimization techniques, have been im-mensely applied in desalination and water treatment for multi-purpose applications. Modelling desalination and water treatment processes and optimizing the operating condition are few among the many applications. In the current review, paramount applications of AI tools in desali-nation and water treatment have been thoroughly reviewed. In addition, benchmarking ANNs with the conventional modelling approaches were highlighted, along with the shortcomings and challenges expected to associate with these common tools in some complex nature practical ap-plication. It was concluded that the use of AI tools will undoubtedly pave the way in the water sector towards better operation, process automation, and water resources management in an in-creasingly volatile environment. Journal Article Desalination 458 84 96 0011-9164 Artificial intelligence, desalination, machine learning, artificial neural network, genetic algorithms, process automation 15 5 2019 2019-05-15 10.1016/j.desal.2019.02.005 COLLEGE NANME Science and Engineering - Faculty COLLEGE CODE FGSEN Swansea University 2019-03-26T13:51:27.7827587 2019-02-11T07:42:29.2028694 Faculty of Science and Engineering School of Engineering and Applied Sciences - Uncategorised Saif Al Aani 1 Talal Bonny 2 Shadi W. Hasan 3 Nidal Hilal 4 0048789-11022019074457.docx Acceptedv3.docx 2019-02-11T07:44:57.7670000 Output 607282 application/vnd.openxmlformats-officedocument.wordprocessingml.document Accepted Manuscript true 2020-02-22T00:00:00.0000000 true eng
title Can machine language and artificial intelligence revolutionize process automation for water treatment and desalination?
spellingShingle Can machine language and artificial intelligence revolutionize process automation for water treatment and desalination?
Nidal Hilal
title_short Can machine language and artificial intelligence revolutionize process automation for water treatment and desalination?
title_full Can machine language and artificial intelligence revolutionize process automation for water treatment and desalination?
title_fullStr Can machine language and artificial intelligence revolutionize process automation for water treatment and desalination?
title_full_unstemmed Can machine language and artificial intelligence revolutionize process automation for water treatment and desalination?
title_sort Can machine language and artificial intelligence revolutionize process automation for water treatment and desalination?
author_id_str_mv 3acba771241d878c8e35ff464aec0342
author_id_fullname_str_mv 3acba771241d878c8e35ff464aec0342_***_Nidal Hilal
author Nidal Hilal
author2 Saif Al Aani
Talal Bonny
Shadi W. Hasan
Nidal Hilal
format Journal article
container_title Desalination
container_volume 458
container_start_page 84
publishDate 2019
institution Swansea University
issn 0011-9164
doi_str_mv 10.1016/j.desal.2019.02.005
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Engineering and Applied Sciences - Uncategorised{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Engineering and Applied Sciences - Uncategorised
document_store_str 1
active_str 0
description Artificial intelligence (AI) is a powerful tool that is commonly applied in engineering multi-disciplines owing to its functionality to resolve real-world problems where deterministic solutions are arduous to achieve. Revolution in water treatment and desalination process automation has been emerging recently. Several challenges are present in the water sector related to data structur-ing and smart water services through which AI would have great potential once those issues are addressed. The distinctive tools of AI, mainly; artificial neural networks (ANNs), as a regression model, and genetic algorithm (GA), as one of the global optimization techniques, have been im-mensely applied in desalination and water treatment for multi-purpose applications. Modelling desalination and water treatment processes and optimizing the operating condition are few among the many applications. In the current review, paramount applications of AI tools in desali-nation and water treatment have been thoroughly reviewed. In addition, benchmarking ANNs with the conventional modelling approaches were highlighted, along with the shortcomings and challenges expected to associate with these common tools in some complex nature practical ap-plication. It was concluded that the use of AI tools will undoubtedly pave the way in the water sector towards better operation, process automation, and water resources management in an in-creasingly volatile environment.
published_date 2019-05-15T03:59:26Z
_version_ 1763753031668596736
score 11.012656

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