{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T18:24:51Z","timestamp":1776536691785,"version":"3.51.2"},"reference-count":47,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,3,22]],"date-time":"2023-03-22T00:00:00Z","timestamp":1679443200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"SEGi University","award":["SEGiIRF\/2022-Q2\/FoEBEIT\/011"],"award-info":[{"award-number":["SEGiIRF\/2022-Q2\/FoEBEIT\/011"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computation"],"abstract":"<jats:p>Desalination is a sustainable method to solve global water scarcity. A Response Surface Methodology (RSM) approach is widely applied to optimize the desalination performance, but further investigations with additional inputs are restricted. An Artificial neuron network (ANN) method is proposed to reconstruct the parameters and demonstrate multivariate analysis. Graphene oxide (GO) content, Polyhedral Oligomeric Silsesquioxane (POSS) content, operating pressure, and salinity were combined as input parameters for a four-dimensional regression analysis to predict the three responses: contact angle, salt rejection, and permeation flux. Average coefficient of determination (R2) values ranged between 0.918 and 0.959. A mathematical equation was derived to find global max and min values. Three objective functions and three-dimensional diagrams were applied to optimize effective cost conditions. It served as the database for the membranologists to decide the amount of GO to be used to fabricate membranes by considering the effects of operating conditions such as salinity and pressure to achieve the desired salt rejection, permeation flux, contact angle, and cost. The finding suggested that a membrane with 0.0063 wt% of GO, operated at 14.2 atm for a 5501 ppm salt solution, is the preferred optimal condition to achieve high salt rejection and permeation flux simultaneously.<\/jats:p>","DOI":"10.3390\/computation11030068","type":"journal-article","created":{"date-parts":[[2023,3,22]],"date-time":"2023-03-22T07:46:43Z","timestamp":1679471203000},"page":"68","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Artificial Neural Network Model for Membrane Desalination: A Predictive and Optimization Study"],"prefix":"10.3390","volume":"11","author":[{"given":"MieowKee","family":"Chan","sequence":"first","affiliation":[{"name":"Centre for Water Research, Faculty of Engineering, Built Environment and Information Technology, SEGi University, Jalan Teknologi, Kota Damansara, Petaling Jaya 47810, Selangor, Malaysia"}]},{"given":"Amin","family":"Shams","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, Faculty of Civil Engineering, Semnan University, Semnan 35131-19111, Iran"}]},{"given":"ChanChin","family":"Wang","sequence":"additional","affiliation":[{"name":"Centre for Modelling and Simulation, Faculty of Engineering, Built Environment and Information Technology, SEGi University, Jalan Teknologi, Kota Damansara, Petaling Jaya 47810, Selangor, Malaysia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3197-7207","authenticated-orcid":false,"given":"PeiYi","family":"Lee","sequence":"additional","affiliation":[{"name":"Centre for Water Research, Faculty of Engineering, Built Environment and Information Technology, SEGi University, Jalan Teknologi, Kota Damansara, Petaling Jaya 47810, Selangor, Malaysia"}]},{"given":"Yousef","family":"Jahani","sequence":"additional","affiliation":[{"name":"Department of Plastic, Faculty of Processing, Iran Polymer and Petrochemical Institute, Pajoohesh Blvd, District 22, Tehran 14977-13115, Iran"}]},{"given":"Seyyed Ahmad","family":"Mirbagheri","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, K. N. Toosi University of Technology, No. 1346, Vali Asr Street, Mirdamad Intersection, Tehran 19697-64499, Iran"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.desal.2019.02.008","article-title":"Reverse osmosis desalination: A state-of-the-art review","volume":"459","author":"Qasim","year":"2019","journal-title":"Desalination"},{"key":"ref_2","first-page":"174","article-title":"Recent progresses in preparation and characterization of RO membranes","volume":"3","author":"Khulbe","year":"2017","journal-title":"J. Membr. Sci. Res."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.jiec.2019.01.045","article-title":"A review of polymeric nanocomposite membranes for water purification","volume":"73","author":"Bassyouni","year":"2019","journal-title":"J. Ind. Eng. Chem."},{"key":"ref_4","unstructured":"Ma, H., and Hsiao, B.S. (2019). 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