{"id":"https://openalex.org/W7123356643","doi":"https://doi.org/10.1109/access.2026.3653004","title":"Physics-Informed Data-Driven Modeling of HVAC Systems: A Systematic Analysis","display_name":"Physics-Informed Data-Driven Modeling of HVAC Systems: A Systematic Analysis","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7123356643","doi":"https://doi.org/10.1109/access.2026.3653004"},"language":null,"primary_location":{"id":"doi:10.1109/access.2026.3653004","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3653004","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3653004","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5066310251","display_name":"Nam Thi Que Nguyen","orcid":null},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nam T. Nguyen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, College of Engineering and Computer Science, University of Central Florida, Orlando, FL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, College of Engineering and Computer Science, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122858223","display_name":"Binh Nguyen","orcid":null},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Binh Nguyen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, College of Engineering and Computer Science, University of Central Florida, Orlando, FL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, College of Engineering and Computer Science, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021671983","display_name":"Truong X. Nghiem","orcid":"https://orcid.org/0000-0003-4841-3800"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Truong X. Nghiem","raw_affiliation_strings":["Department of Electrical and Computer Engineering, College of Engineering and Computer Science, University of Central Florida, Orlando, FL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, College of Engineering and Computer Science, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5066310251"],"corresponding_institution_ids":["https://openalex.org/I106165777"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":58.0547,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.99544812,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"14","issue":null,"first_page":"6481","last_page":"6500"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.972599983215332,"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"}},"topics":[{"id":"https://openalex.org/T11206","display_name":"Model Reduction and Neural Networks","score":0.972599983215332,"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/T10121","display_name":"Building Energy and Comfort Optimization","score":0.00839999970048666,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.0017999999690800905,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/hvac","display_name":"HVAC","score":0.9588000178337097},{"id":"https://openalex.org/keywords/air-conditioning","display_name":"Air conditioning","score":0.6200000047683716},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.5016000270843506},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4690000116825104},{"id":"https://openalex.org/keywords/system-dynamics","display_name":"System dynamics","score":0.43959999084472656},{"id":"https://openalex.org/keywords/systems-modeling","display_name":"Systems modeling","score":0.3799000084400177},{"id":"https://openalex.org/keywords/physical-system","display_name":"Physical system","score":0.37959998846054077}],"concepts":[{"id":"https://openalex.org/C122346748","wikidata":"https://www.wikidata.org/wiki/Q1798773","display_name":"HVAC","level":3,"score":0.9588000178337097},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7483000159263611},{"id":"https://openalex.org/C103742991","wikidata":"https://www.wikidata.org/wiki/Q173725","display_name":"Air conditioning","level":2,"score":0.6200000047683716},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5188000202178955},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.5016000270843506},{"id":"https://openalex.org/C133731056","wikidata":"https://www.wikidata.org/wiki/Q4917288","display_name":"Control engineering","level":1,"score":0.4781000018119812},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4690000116825104},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46209999918937683},{"id":"https://openalex.org/C77405623","wikidata":"https://www.wikidata.org/wiki/Q598451","display_name":"System dynamics","level":2,"score":0.43959999084472656},{"id":"https://openalex.org/C110963975","wikidata":"https://www.wikidata.org/wiki/Q12070446","display_name":"Systems modeling","level":2,"score":0.3799000084400177},{"id":"https://openalex.org/C116672817","wikidata":"https://www.wikidata.org/wiki/Q1454986","display_name":"Physical system","level":2,"score":0.37959998846054077},{"id":"https://openalex.org/C55037315","wikidata":"https://www.wikidata.org/wiki/Q5421151","display_name":"Experimental data","level":2,"score":0.37299999594688416},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.366100013256073},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.33559998869895935},{"id":"https://openalex.org/C2780331096","wikidata":"https://www.wikidata.org/wiki/Q24965464","display_name":"Energy modeling","level":3,"score":0.3163999915122986},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.31360000371932983},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.3077000081539154},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.2903999984264374},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.265500009059906}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/access.2026.3653004","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3653004","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3653004","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3653004","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.7835443615913391}],"awards":[{"id":"https://openalex.org/G5353340311","display_name":null,"funder_award_id":"2514584","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8664243642","display_name":null,"funder_award_id":"2513096","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W1971735090","https://openalex.org/W1984481057","https://openalex.org/W1988101164","https://openalex.org/W1997055709","https://openalex.org/W2005289033","https://openalex.org/W2032589491","https://openalex.org/W2058294246","https://openalex.org/W2059040987","https://openalex.org/W2068141066","https://openalex.org/W2107794518","https://openalex.org/W2125406789","https://openalex.org/W2138655319","https://openalex.org/W2139923370","https://openalex.org/W2140246545","https://openalex.org/W2163121678","https://openalex.org/W2194775991","https://openalex.org/W2243194968","https://openalex.org/W2594728989","https://openalex.org/W2620512989","https://openalex.org/W2768748954","https://openalex.org/W2798274031","https://openalex.org/W2956808672","https://openalex.org/W2972574632","https://openalex.org/W2974916071","https://openalex.org/W2979786244","https://openalex.org/W2986587829","https://openalex.org/W2988290754","https://openalex.org/W3017305623","https://openalex.org/W3021449555","https://openalex.org/W3028073062","https://openalex.org/W3090789943","https://openalex.org/W3115889371","https://openalex.org/W3128157635","https://openalex.org/W3156755729","https://openalex.org/W3163993681","https://openalex.org/W3185585276","https://openalex.org/W3201666041","https://openalex.org/W3217738881","https://openalex.org/W4211049957","https://openalex.org/W4252208101","https://openalex.org/W4283219895","https://openalex.org/W4285092337","https://openalex.org/W4286781802","https://openalex.org/W4310881476","https://openalex.org/W4312181927","https://openalex.org/W4315489085","https://openalex.org/W4322766057","https://openalex.org/W4361215660","https://openalex.org/W4367309343","https://openalex.org/W4382935812","https://openalex.org/W4385128273","https://openalex.org/W4391307667","https://openalex.org/W4396941366","https://openalex.org/W4401889742","https://openalex.org/W4402699269","https://openalex.org/W4405660012","https://openalex.org/W4406237488","https://openalex.org/W4406277239","https://openalex.org/W4408821765","https://openalex.org/W4409370481","https://openalex.org/W4410351908","https://openalex.org/W4410483840","https://openalex.org/W4411992700","https://openalex.org/W4413392834","https://openalex.org/W4413743241","https://openalex.org/W4414065180","https://openalex.org/W4415531263","https://openalex.org/W4415535116","https://openalex.org/W7081932357"],"related_works":[],"abstract_inverted_index":{"Heating,":[0],"ventilation,":[1],"and":[2,37,85,110,130,143,161,184,189,225],"air":[3],"conditioning":[4],"(HVAC)":[5],"systems":[6,167],"account":[7],"for":[8,24,98,164,181,238,243],"a":[9,175],"significant":[10],"portion":[11],"of":[12,52,113,115,153,158,210],"energy":[13],"consumption":[14],"in":[15,48,156,193,205],"developed":[16,97],"countries.":[17],"Accurately":[18],"identifying":[19],"their":[20],"dynamics":[21,51,209],"is":[22,30,75,218],"crucial":[23],"developing":[25],"effective":[26],"controllers.":[27],"However,":[28,60],"it":[29],"challenging":[31],"due":[32],"to":[33,67,106,148],"the":[34,50,72,108,144,151,207,215,235],"system\u2019s":[35],"nonlinearities":[36],"variations":[38],"across":[39],"building":[40],"types.":[41],"Data-driven":[42],"approaches":[43,142],"have":[44,95],"shown":[45],"great":[46],"promise":[47],"modeling":[49,114,146,165,191],"HVAC":[53,166,177,211,244],"systems,":[54,212],"replacing":[55],"traditional":[56],"ordinary":[57],"differential":[58],"equations.":[59],"relying":[61],"solely":[62],"on":[63],"data":[64,74,111,162,172,217],"can":[65],"lead":[66],"poor":[68],"generalization,":[69],"particularly":[70],"when":[71,78,214],"training":[73,216],"limited":[76],"or":[77,221],"unknown":[79],"disturbances,":[80],"such":[81],"as":[82],"weather":[83],"conditions":[84],"occupant":[86],"behavior,":[87],"are":[88,135,179,234],"present.":[89],"Physics-informed":[90],"machine":[91,103,139,240],"learning":[92,104,140,241],"(PIML)":[93],"techniques":[94,122,192],"been":[96],"integrating":[99],"physical":[100,126,232],"principles":[101],"into":[102],"methods":[105,201],"improve":[107],"accuracy":[109],"efficiency":[112,163],"dynamical":[116],"systems.":[117],"This":[118],"paper":[119],"investigates":[120],"PIML":[121,154,190,200],"incorporating":[123],"three":[124],"different":[125,194],"properties:":[127],"monotonicity,":[128],"boundedness,":[129],"system":[131,178,245],"structure.":[132],"These":[133],"models":[134,155,204],"benchmarked":[136],"against":[137],"physics-agnostic":[138],"(PAML)":[141],"gray-box":[145],"technique":[147],"further":[149],"highlight":[150],"performance":[152,242],"terms":[157],"accuracy,":[159],"robustness,":[160],"from":[168,174],"real":[169],"data.":[170],"Experimental":[171],"collected":[173],"real-world":[176],"used":[180],"systematically":[182],"studying":[183],"analyzing":[185],"thirteen":[186],"gray-box,":[187],"PAML,":[188],"scenarios.":[195],"Our":[196],"results":[197],"demonstrate":[198],"that":[199],"outperform":[202],"PAML":[203],"predicting":[206],"temperature":[208],"especially":[213],"limited,":[219],"unreliable,":[220],"noisy,":[222],"with":[223],"accurate":[224],"robust":[226],"performance.":[227],"Furthermore,":[228],"we":[229],"identify":[230],"which":[231],"properties":[233],"most":[236],"beneficial":[237],"enhancing":[239],"identification.":[246]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2026-01-14T00:00:00"}