{"id":"https://openalex.org/W4400519611","doi":"https://doi.org/10.1016/j.csite.2024.104820","title":"Efficiency increment of CFD modeling by using ANFIS artificial intelligence for thermal-based separation modeling","display_name":"Efficiency increment of CFD modeling by using ANFIS artificial intelligence for thermal-based separation modeling","publication_year":2024,"publication_date":"2024-07-11","ids":{"openalex":"https://openalex.org/W4400519611","doi":"https://doi.org/10.1016/j.csite.2024.104820"},"language":"en","primary_location":{"id":"doi:10.1016/j.csite.2024.104820","doi":"https://doi.org/10.1016/j.csite.2024.104820","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.csite.2024.104820","pdf_url":null,"source":{"id":"https://openalex.org/S2764363796","display_name":"Case Studies in Thermal Engineering","issn_l":"2214-157X","issn":["2214-157X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-b","jufo-1","norway-1","oarl","poland-70"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Case Studies in Thermal Engineering","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1016/j.csite.2024.104820","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034038080","display_name":"Bizhou Ye","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I4210113795","display_name":"Hubei University of Arts and Science","ror":"https://ror.org/0212jcf64","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210113795"]},{"id":"https://openalex.org/I4405280043","display_name":"Science and Technology College of Hubei University of Arts and Science","ror":"https://ror.org/02bnqxp96","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405280043"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bizhou Ye","raw_affiliation_strings":["School of the Electronic Science and Information Engineering, Science and Technology College of Hubei University of Arts and Sciences, Xiangyang, Hubei, 441000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of the Electronic Science and Information Engineering, Science and Technology College of Hubei University of Arts and Sciences, Xiangyang, Hubei, 441000, China","institution_ids":["https://openalex.org/I4210113795","https://openalex.org/I4405280043"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101901570","display_name":"Wei Zhou","orcid":"https://orcid.org/0000-0002-1641-1408","observed_orcids":["https://orcid.org/0000-0002-1641-1408"]},"institutions":[{"id":"https://openalex.org/I4210113795","display_name":"Hubei University of Arts and Science","ror":"https://ror.org/0212jcf64","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210113795"]},{"id":"https://openalex.org/I4405280043","display_name":"Science and Technology College of Hubei University of Arts and Science","ror":"https://ror.org/02bnqxp96","country_code":"CN","type":"education","lineage":["https://openalex.org/I4405280043"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wei Zhou","raw_affiliation_strings":["Science and Technology College of Hubei University of Arts and Sciences, Xiangyang, Hubei, 441000, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Science and Technology College of Hubei University of Arts and Sciences, Xiangyang, Hubei, 441000, China","institution_ids":["https://openalex.org/I4210113795","https://openalex.org/I4405280043"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101901570"],"corresponding_institution_ids":["https://openalex.org/I4210113795","https://openalex.org/I4405280043"],"apc_list":{"value":1210,"currency":"USD","value_usd":1210},"apc_paid":{"value":1210,"currency":"USD","value_usd":1210},"fwci":1.4455,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.77680111,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"60","issue":null,"first_page":"104820","last_page":"104820"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10197","display_name":"Membrane Separation Technologies","score":0.9458000063896179,"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"}},"topics":[{"id":"https://openalex.org/T10197","display_name":"Membrane Separation Technologies","score":0.9458000063896179,"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/T11206","display_name":"Model Reduction and Neural Networks","score":0.009700000286102295,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.007499999832361937,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/vacuum-membrane-distillation","display_name":"vacuum membrane distillation","score":0.9980000257492065},{"id":"https://openalex.org/keywords/temperature-prediction","display_name":"temperature prediction","score":0.8209999799728394},{"id":"https://openalex.org/keywords/adaptive-neuro-fuzzy-inference-system","display_name":"adaptive neuro-fuzzy inference system","score":0.8759999871253967},{"id":"https://openalex.org/keywords/kernel-ridge-regression","display_name":"kernel ridge regression","score":0.8799999952316284},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"multilayer perceptron","score":0.9750000238418579}],"concepts":[{"id":"https://openalex.org/C186108316","wikidata":"https://www.wikidata.org/wiki/Q352530","display_name":"Adaptive neuro fuzzy inference system","level":4,"score":0.9060773253440857},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6192403435707092},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5647132396697998},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.542288601398468},{"id":"https://openalex.org/C1633027","wikidata":"https://www.wikidata.org/wiki/Q815820","display_name":"Computational fluid dynamics","level":2,"score":0.5266951322555542},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.5085817575454712},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.49619704484939575},{"id":"https://openalex.org/C2777115002","wikidata":"https://www.wikidata.org/wiki/Q7168246","display_name":"Performance prediction","level":2,"score":0.47806838154792786},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.44472044706344604},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.4192373752593994},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.2994874119758606},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.15833306312561035},{"id":"https://openalex.org/C195975749","wikidata":"https://www.wikidata.org/wiki/Q1475705","display_name":"Fuzzy control system","level":3,"score":0.155775249004364},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13861680030822754},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.csite.2024.104820","doi":"https://doi.org/10.1016/j.csite.2024.104820","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.csite.2024.104820","pdf_url":null,"source":{"id":"https://openalex.org/S2764363796","display_name":"Case Studies in Thermal Engineering","issn_l":"2214-157X","issn":["2214-157X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-b","jufo-1","norway-1","oarl","poland-70"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Case Studies in Thermal Engineering","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:44987c57e39c445681428a679e82c0f1","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/44987c57e39c445681428a679e82c0f1","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Case Studies in Thermal Engineering, Vol 60, Iss , Pp 104820- (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1016/j.csite.2024.104820","doi":"https://doi.org/10.1016/j.csite.2024.104820","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.csite.2024.104820","pdf_url":null,"source":{"id":"https://openalex.org/S2764363796","display_name":"Case Studies in Thermal Engineering","issn_l":"2214-157X","issn":["2214-157X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-b","jufo-1","norway-1","oarl","poland-70"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Case Studies in Thermal Engineering","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W176909285","https://openalex.org/W1736905284","https://openalex.org/W1977364986","https://openalex.org/W1995714897","https://openalex.org/W2002091023","https://openalex.org/W2019207321","https://openalex.org/W2078718287","https://openalex.org/W2106875937","https://openalex.org/W2904298560","https://openalex.org/W2913332651","https://openalex.org/W2939603635","https://openalex.org/W2992885437","https://openalex.org/W3008896913","https://openalex.org/W3017060530","https://openalex.org/W3097629404","https://openalex.org/W4281788624","https://openalex.org/W4293248431","https://openalex.org/W4304687880","https://openalex.org/W4313398934","https://openalex.org/W4320340699","https://openalex.org/W4390534529","https://openalex.org/W4391046452","https://openalex.org/W4394769661","https://openalex.org/W4394844410","https://openalex.org/W4394876044","https://openalex.org/W4398200345","https://openalex.org/W4399831362"],"related_works":["https://openalex.org/W4403436293","https://openalex.org/W2982257420","https://openalex.org/W4396618091","https://openalex.org/W7213768608","https://openalex.org/W1450985564","https://openalex.org/W4389336045","https://openalex.org/W4376320873","https://openalex.org/W4293248431","https://openalex.org/W4280603166","https://openalex.org/W4394606040"],"abstract_inverted_index":{"This":[0],"study":[1],"presents":[2],"a":[3,11,63,160,165,177,186],"comprehensive":[4],"analysis":[5],"of":[6,147,162,167,171,183,189],"predicting":[7],"the":[8,40,44,113,118,129,150,156],"temperature":[9,37,46],"in":[10,39,107,111],"vacuum":[12],"membrane":[13],"distillation":[14],"(VMD)":[15],"process.":[16],"The":[17,55,137,169],"simulation":[18],"was":[19,33,47,90,115,126,173],"carried":[20],"out":[21],"via":[22],"computational":[23],"fluid":[24],"dynamics":[25],"(CFD)":[26],"as":[27,29],"well":[28],"machine":[30,52],"learning.":[31],"CFD":[32],"performed":[34],"for":[35,49,66,92,123],"obtaining":[36],"distribution":[38],"feed":[41],"solution,":[42],"and":[43,85,99,153,164,185],"calculated":[45],"used":[48],"training":[50,151],"several":[51],"learning":[53],"models.":[54,120],"dataset":[56],"comprises":[57],"over":[58],"13,000":[59],"observations,":[60],"which":[61],"provide":[62],"rich":[64],"source":[65],"modeling":[67],"complex":[68],"relationships.":[69],"Three":[70],"sophisticated":[71],"regression":[72],"models":[73,125],"were":[74],"employed:":[75],"Adaptive":[76],"Neuro-Fuzzy":[77],"Inference":[78],"System":[79],"(ANFIS),":[80],"Kernel":[81],"Ridge":[82],"Regression":[83],"(KRR),":[84],"Multi-Layer":[86],"Perceptron":[87],"(MLP).":[88],"ANFIS":[89,109,138,172],"chosen":[91],"its":[93],"hybrid":[94],"nature,":[95],"combining":[96],"neural":[97],"networks":[98],"fuzzy":[100],"logic,":[101],"effectively":[102],"capturing":[103],"intricate":[104],"non-linear":[105],"relationships":[106],"data.":[108],"performance":[110,142],"fitting":[112],"data":[114],"compared":[116],"with":[117,143],"other":[119],"Hyper-parameter":[121],"optimization":[122],"these":[124],"conducted":[127],"using":[128],"Tabu":[130],"Search":[131],"algorithm":[132],"to":[133],"ensure":[134],"optimal":[135],"performance.":[136],"model":[139],"demonstrated":[140],"superior":[141],"an":[144],"R2":[145,181],"score":[146,182],"0.9964513":[148],"on":[149,155],"set":[152],"0.9964507":[154],"test":[157],"set,":[158],"alongside":[159],"MSE":[161],"0.037655":[163],"MAE":[166],"0.168272.":[168],"robustness":[170],"further":[174],"confirmed":[175],"by":[176],"3-fold":[178],"cross-validation":[179],"mean":[180],"0.9964579":[184],"standard":[187],"deviation":[188],"3.3619616e\u221205.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":3}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2024-07-12T00:00:00"}
