{"id":"https://openalex.org/W4406470859","doi":"https://doi.org/10.3390/w17020227","title":"Artificial Neural Networks (ANNs) and Multiple Linear Regression (MLR) Analysis Modelling for Predicting Chemical Dosages of a Water Treatment Plant (WTP) of Drinking Water","display_name":"Artificial Neural Networks (ANNs) and Multiple Linear Regression (MLR) Analysis Modelling for Predicting Chemical Dosages of a Water Treatment Plant (WTP) of Drinking Water","publication_year":2025,"publication_date":"2025-01-16","ids":{"openalex":"https://openalex.org/W4406470859","doi":"https://doi.org/10.3390/w17020227"},"language":"en","primary_location":{"id":"doi:10.3390/w17020227","doi":"https://doi.org/10.3390/w17020227","is_oa":true,"landing_page_url":"https://doi.org/10.3390/w17020227","pdf_url":"https://www.mdpi.com/2073-4441/17/2/227/pdf?version=1737096123","source":{"id":"https://openalex.org/S134216166","display_name":"Water","issn_l":"2073-4441","issn":["2073-4441"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Water","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2073-4441/17/2/227/pdf?version=1737096123","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5024913643","display_name":"STYLIANOS GYPARAKIS","orcid":"https://orcid.org/0000-0001-5314-6060","observed_orcids":["https://orcid.org/0000-0001-5314-6060"]},"institutions":[{"id":"https://openalex.org/I55741626","display_name":"Technical University of Crete","ror":"https://ror.org/03f8bz564","country_code":"GR","type":"education","lineage":["https://openalex.org/I55741626"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Stylianos Gyparakis","raw_affiliation_strings":["School of Chemical and Environmental Engineering, Technical University of Crete, 73100 Chania, Greece"],"raw_orcid":"https://orcid.org/0000-0001-5314-6060","affiliations":[{"raw_affiliation_string":"School of Chemical and Environmental Engineering, Technical University of Crete, 73100 Chania, Greece","institution_ids":["https://openalex.org/I55741626"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036664661","display_name":"Ioannis C. Trichakis","orcid":"https://orcid.org/0000-0002-1463-8625","observed_orcids":["https://orcid.org/0000-0002-1463-8625"]},"institutions":[{"id":"https://openalex.org/I4210118689","display_name":"Joint Research Centre","ror":"https://ror.org/02qezmz13","country_code":"IT","type":"government","lineage":["https://openalex.org/I1320481043","https://openalex.org/I2800387288","https://openalex.org/I4210118689","https://openalex.org/I4210161702"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Ioannis Trichakis","raw_affiliation_strings":["European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy"],"raw_orcid":"https://orcid.org/0000-0002-1463-8625","affiliations":[{"raw_affiliation_string":"European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy","institution_ids":["https://openalex.org/I4210118689"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012902879","display_name":"Tryfon Daras","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I55741626","display_name":"Technical University of Crete","ror":"https://ror.org/03f8bz564","country_code":"GR","type":"education","lineage":["https://openalex.org/I55741626"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Tryfon Daras","raw_affiliation_strings":["School of Chemical and Environmental Engineering, Technical University of Crete, 73100 Chania, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Chemical and Environmental Engineering, Technical University of Crete, 73100 Chania, Greece","institution_ids":["https://openalex.org/I55741626"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091660580","display_name":"Evan Diamadopoulos","orcid":"https://orcid.org/0000-0003-1535-8534","observed_orcids":["https://orcid.org/0000-0003-1535-8534"]},"institutions":[{"id":"https://openalex.org/I55741626","display_name":"Technical University of Crete","ror":"https://ror.org/03f8bz564","country_code":"GR","type":"education","lineage":["https://openalex.org/I55741626"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Evan Diamadopoulos","raw_affiliation_strings":["School of Chemical and Environmental Engineering, Technical University of Crete, 73100 Chania, Greece"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Chemical and Environmental Engineering, Technical University of Crete, 73100 Chania, Greece","institution_ids":["https://openalex.org/I55741626"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5036664661"],"corresponding_institution_ids":["https://openalex.org/I4210118689"],"apc_list":{"value":2600,"currency":"CHF","value_usd":3137},"apc_paid":{"value":2600,"currency":"CHF","value_usd":3137},"fwci":3.7203,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.93792879,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"17","issue":"2","first_page":"227","last_page":"227"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.5228999853134155,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11490","display_name":"Hydrological Forecasting Using AI","score":0.5228999853134155,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11188","display_name":"Coagulation and Flocculation Studies","score":0.12449999898672104,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11493","display_name":"Water Treatment and Disinfection","score":0.062300000339746475,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.8600000143051147},{"id":"https://openalex.org/keywords/multiple-linear-regression","display_name":"multiple linear regression","score":0.9789999723434448},{"id":"https://openalex.org/keywords/drinking-water-treatment","display_name":"drinking water treatment","score":0.6269999742507935},{"id":"https://openalex.org/keywords/ozone-dose","display_name":"ozone dosage","score":0.5580000281333923},{"id":"https://openalex.org/keywords/chlorine-dosing","display_name":"chlorine dosage","score":0.9829999804496765},{"id":"https://openalex.org/keywords/neural-network-ensembles","display_name":"neural network ensembles","score":0.6830000281333923},{"id":"https://openalex.org/keywords/model-comparison","display_name":"model comparison","score":0.7179999947547913},{"id":"https://openalex.org/keywords/water-quality-parameters","display_name":"water quality parameters","score":0.6430000066757202}],"concepts":[{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6784399151802063},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.6500120162963867},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.515067994594574},{"id":"https://openalex.org/C162156334","wikidata":"https://www.wikidata.org/wiki/Q473420","display_name":"Dose","level":2,"score":0.5114508867263794},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.49091821908950806},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.48321807384490967},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.44646501541137695},{"id":"https://openalex.org/C190960625","wikidata":"https://www.wikidata.org/wiki/Q1058719","display_name":"Water treatment","level":2,"score":0.4319288432598114},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.40052175521850586},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.39091241359710693},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.3668827712535858},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2532801628112793},{"id":"https://openalex.org/C87717796","wikidata":"https://www.wikidata.org/wiki/Q146326","display_name":"Environmental engineering","level":1,"score":0.22674167156219482},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.1926887333393097},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.10194668173789978},{"id":"https://openalex.org/C98274493","wikidata":"https://www.wikidata.org/wiki/Q128406","display_name":"Pharmacology","level":1,"score":0.0},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3390/w17020227","doi":"https://doi.org/10.3390/w17020227","is_oa":true,"landing_page_url":"https://doi.org/10.3390/w17020227","pdf_url":"https://www.mdpi.com/2073-4441/17/2/227/pdf?version=1737096123","source":{"id":"https://openalex.org/S134216166","display_name":"Water","issn_l":"2073-4441","issn":["2073-4441"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Water","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3390/w17020227","doi":"https://doi.org/10.3390/w17020227","is_oa":true,"landing_page_url":"https://doi.org/10.3390/w17020227","pdf_url":"https://www.mdpi.com/2073-4441/17/2/227/pdf?version=1737096123","source":{"id":"https://openalex.org/S134216166","display_name":"Water","issn_l":"2073-4441","issn":["2073-4441"],"is_oa":true,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Water","raw_type":"journal-article"},"sustainable_development_goals":[{"score":1.0,"id":"https://metadata.un.org/sdg/6","display_name":"Clean water and sanitation"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4406470859.pdf","grobid_xml":"https://content.openalex.org/works/W4406470859.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W2008117486","https://openalex.org/W2058998445","https://openalex.org/W2560734925","https://openalex.org/W2787420210","https://openalex.org/W2787473679","https://openalex.org/W2894855153","https://openalex.org/W3028198528","https://openalex.org/W3049235151","https://openalex.org/W3090868346","https://openalex.org/W3099865851","https://openalex.org/W4200144750","https://openalex.org/W4281256190","https://openalex.org/W4281262741","https://openalex.org/W4283376185","https://openalex.org/W4296955431","https://openalex.org/W4312214431","https://openalex.org/W4319295184","https://openalex.org/W4377021898","https://openalex.org/W4382753233","https://openalex.org/W4382793105","https://openalex.org/W4383066642","https://openalex.org/W4383955221","https://openalex.org/W4384922208","https://openalex.org/W4386960690","https://openalex.org/W4388821837","https://openalex.org/W4394744775","https://openalex.org/W4396821763","https://openalex.org/W4399976056","https://openalex.org/W4401017704","https://openalex.org/W4403251718","https://openalex.org/W4404586756"],"related_works":["https://openalex.org/W2119960866","https://openalex.org/W3160101930","https://openalex.org/W2964327398","https://openalex.org/W7005115305","https://openalex.org/W4404970883","https://openalex.org/W4403251718","https://openalex.org/W2166155771","https://openalex.org/W4309745911","https://openalex.org/W3170556431","https://openalex.org/W3018552033"],"abstract_inverted_index":{"As":[0,156],"the":[1,9,17,29,45,57,69,79,85,91,121,135,139,144,152,172,179,198,207,227,235,245,251,281,284,294,308,324,327,337,340,346,354,362,372,395,398,404,409],"quantity":[2],"and":[3,13,90,117,151,162,191,224,268,275,389,392],"quality":[4,25,163],"of":[5,16,19,52,87,106,197,202,247,283,353,384,408],"water":[6,27,164,204,387],"resources":[7],"decreases,":[8],"need":[10],"for":[11,28,178,213,239,293,381],"timely":[12],"valid":[14],"prediction":[15,39,72,282],"WTP":[18,51,160,201,383],"drinking":[20,26,53,203,386],"water-used":[21],"chemicals":[22],"to":[23,169,222,234,306,315,322,361],"produce":[24],"final":[30],"consumer":[31],"increases.":[32],"The":[33,61,74],"question":[34],"that":[35,374],"arises":[36],"is":[37,64,320,343,403],"which":[38,104,210,402],"model":[40,101,174,229,238,287],"performs":[41],"better":[42,176,212,231,321],"in":[43,49,127,256,334,356,365],"predicting":[44,257],"chemical":[46,400],"dosages":[47],"used":[48,200,399],"a":[50,65,382,385],"water.":[54],"ANNs":[55,375],"or":[56,312],"MLR":[58,128,173,236,285],"analysis":[59,129,237,286],"models?":[60],"present":[62],"study":[63,67,369],"comparative":[66],"between":[68],"two":[70],"aforementioned":[71],"models.":[73],"evaluation":[75],"criteria":[76],"chosen":[77],"are:":[78],"Root":[80],"Mean":[81],"Square":[82],"Error":[83],"(RMSE),":[84],"Coefficient":[86,94],"Determination":[88],"(R2),":[89],"Pearson":[92],"Correlation":[93],"(R).":[95],"A":[96],"previously":[97],"optimised":[98],"ensemble":[99],"ANN":[100,208,228,252],"was":[102,254,288],"chosen,":[103],"consisted":[105],"100":[107],"neural":[108],"networks,":[109],"with":[110,130,326,339],"42":[111],"hidden":[112],"nodes":[113],"each,":[114],"10":[115,159],"inputs,":[116],"4":[118],"outputs.":[119],"On":[120],"other":[122],"hand,":[123],"four":[124,199,241],"different":[125],"scenarios":[126,314],"dependent":[131],"variables":[132,165],"were":[133,166],"examined:":[134],"ozone":[136,347],"(O3)":[137],"concentration,":[138],"Anionic":[140],"Polyelectrolyte":[141],"(ANPE)":[142],"dosage,":[143,150],"Poly-Aluminium":[145],"Chloride":[146],"hydroxide":[147],"sulphate":[148],"(PACl)":[149],"chlorine":[153],"(Cl2(g))":[154],"dosage.":[155],"independent":[157],"variables,":[158],"operational":[161],"considered.":[167],"According":[168,221],"RMSE":[170,186,192],"results,":[171,226],"had":[175,230],"performance":[177,232,253],"three":[180,258],"(RMSE":[181,216],"ANPE":[182,260],"=":[183,188,194,218,262,266,272,277,298,301],"0.05":[184],"mg/L,":[185,190],"PACl":[187,264],"0.08":[189],"Cl2(g)":[193,269,295,317],"0.10":[195],"kg/h)":[196],"chemicals,":[205],"than":[206],"model,":[209],"performed":[211],"only":[214,292],"one":[215,325,338],"O3":[217],"0.02":[219],"mg/L).":[220],"R2":[223,248],"R":[225,276,300],"compared":[233],"all":[240,357],"variables.":[242],"Based":[243],"on":[244],"criterion":[246],">":[249],"0.5,":[250],"satisfactory":[255,291],"variables:":[259],"(R2":[261,265,271,297],"0.772),":[263],"0.742),":[267],"dosage":[270,296],"0.838,":[273],"+23%":[274],"0.91553,":[278],"+11%).":[279],"Respectively,":[280],"evaluated":[289],"as":[290],"0.681,":[299],"0.82500).":[302],"If":[303,330],"someone":[304],"wants":[305],"use":[307,323],"above":[309],"described":[310],"(ANN":[311],"MLR)":[313],"predict":[316],"dosages,":[318,401],"it":[319],"smallest":[328],"RMSE.":[329],"they":[331],"are":[332,376],"interested":[333],"fitting":[335],"purposes,":[336],"largest":[341],"R2,":[342,355],"preferable.":[344],"Also,":[345],"concentration":[348],"variable":[349],"showed":[350],"low":[351],"values":[352],"cases,":[358],"possibly":[359],"due":[360],"large":[363],"variation":[364],"its":[366],"values.":[367],"This":[368],"further":[370],"strengthens":[371],"opinion":[373],"useful":[377],"decision":[378],"support":[379],"tools":[380],"operator":[388],"can":[390],"accurately":[391],"sufficiently":[393],"mimic":[394],"decisions":[396],"regarding":[397],"main":[405],"daily":[406],"concern":[407],"plant":[410],"operator.":[411]},"counts_by_year":[{"year":2026,"cited_by_count":10},{"year":2025,"cited_by_count":6}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2025-01-17T00:00:00"}
