A comprehensive review on modelling the adsorption process for heavy metal removal from waste water using artificial neural network technique
Seef Saadi Fiyadh,
Saja Mohsen Alardhi,
Mohamed Al Omar,
Mustafa M. Aljumaily,
Mohammed Abdulhakim Al Saadi,
Sabah Saadi Fayaed,
Sulaiman Nayef Ahmed,
Ali Dawood Salman,
Alyaa H. Abdalsalm,
Noor Mohsen Jabbar,
Ahmed El-Shafi
Affiliations
Seef Saadi Fiyadh
Ministry of Planning, Central Statistical Organization, Anbar, Iraq
Saja Mohsen Alardhi
Nanotechnology and Advanced Materials Research Center, University of Technology, Iraq
Mohamed Al Omar
Department of Civil Engineering, Al-Maarif University College, Ramadi, Iraq
Mustafa M. Aljumaily
Department of Civil Engineering, Al-Maarif University College, Ramadi, Iraq
Mohammed Abdulhakim Al Saadi
Department of Civil Engineering, Al-Maarif University College, Ramadi, Iraq
Sabah Saadi Fayaed
Department of Civil Engineering, Al-Maarif University College, Ramadi, Iraq; Ministry of Planning Dept. Social Services Projects Section, Baghdad, Iraq
Sulaiman Nayef Ahmed
Construction and Projects Department, University of Fallujah, Iraq
Ali Dawood Salman
Sustainability Solutions Research Lab, University of Pannonia, Egyetem Str. 10, H-8200 Veszprem, Hungary; Department of Chemical and Petroleum Refining Engineering, College of Oil and Gas Engineering, Basra University for Oil and Gas, Iraq; Corresponding author. Sustainability Solutions Research Lab, University of Pannonia, Egyetem Str. 10, H-8200 Veszprem, Hungary.
Alyaa H. Abdalsalm
Nanotechnology and Advanced Materials Research Center, University of Technology, Iraq
Noor Mohsen Jabbar
Biochemical Engineering Department, Al-Khwarizmi College of Engineering, University of Baghdad, Baghdad, Iraq
Ahmed El-Shafi
Department of Civil Engineering, University of Malaya, Kuala Lumpur, 50603, Malaysia
Water is the most necessary and significant element for all life on earth. Unfortunately, the quality of the water resources is constantly declining as a result of population development, industry, and civilization progress. Due to their extreme toxicity, heavy metals removal from water has drawn researchers' attention. A lot of scientific applications use artificial neural networks (ANNs) because of their excellent ability to map nonlinear relationships. ANNs shown excellent modelling capabilities for the water treatment remediation. The adsorption process uses a variety of variables, making the interaction between them nonlinear. Selecting the best technique can produce excellent results; the adsorption approach for removing heavy metals is highly effective. Different studies show that the ANNs modelling approach can accurately forecast the adsorbed heavy metals and other contaminants in order to remove them.
