{"id":"https://openalex.org/W7106237824","doi":"https://doi.org/10.1061/jccee5.cpeng-7033","title":"Rapid Prediction of Regional Thermal Environment Parameters: A Method Based on Numerical Solution and Machine Learning Extension","display_name":"Rapid Prediction of Regional Thermal Environment Parameters: A Method Based on Numerical Solution and Machine Learning Extension","publication_year":2025,"publication_date":"2025-11-21","ids":{"openalex":"https://openalex.org/W7106237824","doi":"https://doi.org/10.1061/jccee5.cpeng-7033"},"language":"en","primary_location":{"id":"doi:10.1061/jccee5.cpeng-7033","is_oa":false,"landing_page_url":"https://doi.org/10.1061/jccee5.cpeng-7033","pdf_url":null,"source":{"id":"https://openalex.org/S176637136","display_name":"Journal of Computing in Civil Engineering","issn_l":"0887-3801","issn":["0887-3801","1943-5487"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315747","host_organization_name":"American Society of Civil Engineers","host_organization_lineage":["https://openalex.org/P4310315747"],"host_organization_lineage_names":["American Society of Civil Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing in Civil Engineering","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Jiangbo Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jiangbo Li","raw_affiliation_strings":["Guangzhou Univ"],"affiliations":[{"raw_affiliation_string":"Guangzhou Univ","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yixian Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yixian Wang","raw_affiliation_strings":["Guangzhou Univ"],"affiliations":[{"raw_affiliation_string":"Guangzhou Univ","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zhihong Zhai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210118918","display_name":"Climate Centre","ror":"https://ror.org/028x4en59","country_code":"NL","type":"other","lineage":["https://openalex.org/I4210118918"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Zhihong Zhai","raw_affiliation_strings":["Guangzhou Climate and Agrometeorology Center"],"affiliations":[{"raw_affiliation_string":"Guangzhou Climate and Agrometeorology Center","institution_ids":["https://openalex.org/I4210118918"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Haiyan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I4210118918","display_name":"Climate Centre","ror":"https://ror.org/028x4en59","country_code":"NL","type":"other","lineage":["https://openalex.org/I4210118918"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Haiyan Li","raw_affiliation_strings":["Guangzhou Climate and Agrometeorology Center"],"affiliations":[{"raw_affiliation_string":"Guangzhou Climate and Agrometeorology Center","institution_ids":["https://openalex.org/I4210118918"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yunfei Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yunfei Ding","raw_affiliation_strings":["Guangzhou Univ"],"affiliations":[{"raw_affiliation_string":"Guangzhou Univ","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.4967101,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10766","display_name":"Urban Heat Island Mitigation","score":0.9750999808311462,"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/T10766","display_name":"Urban Heat Island Mitigation","score":0.9750999808311462,"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/T10121","display_name":"Building Energy and Comfort Optimization","score":0.007799999788403511,"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/T10266","display_name":"Plant Water Relations and Carbon Dynamics","score":0.00419999985024333,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/microclimate","display_name":"Microclimate","score":0.7675999999046326},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.762499988079071},{"id":"https://openalex.org/keywords/airflow","display_name":"Airflow","score":0.5641999840736389},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.5587999820709229},{"id":"https://openalex.org/keywords/thermal","display_name":"Thermal","score":0.5016000270843506},{"id":"https://openalex.org/keywords/thermal-comfort","display_name":"Thermal comfort","score":0.47920000553131104},{"id":"https://openalex.org/keywords/humidity","display_name":"Humidity","score":0.3955000042915344},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.3905999958515167},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.36010000109672546}],"concepts":[{"id":"https://openalex.org/C32957820","wikidata":"https://www.wikidata.org/wiki/Q215108","display_name":"Microclimate","level":2,"score":0.7675999999046326},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.762499988079071},{"id":"https://openalex.org/C116067010","wikidata":"https://www.wikidata.org/wiki/Q4698686","display_name":"Airflow","level":2,"score":0.5641999840736389},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.5587999820709229},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5410000085830688},{"id":"https://openalex.org/C204530211","wikidata":"https://www.wikidata.org/wiki/Q752823","display_name":"Thermal","level":2,"score":0.5016000270843506},{"id":"https://openalex.org/C133913538","wikidata":"https://www.wikidata.org/wiki/Q774514","display_name":"Thermal comfort","level":2,"score":0.47920000553131104},{"id":"https://openalex.org/C151420433","wikidata":"https://www.wikidata.org/wiki/Q180600","display_name":"Humidity","level":2,"score":0.3955000042915344},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3905999958515167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37860000133514404},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3767000138759613},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.36010000109672546},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3562999963760376},{"id":"https://openalex.org/C158960510","wikidata":"https://www.wikidata.org/wiki/Q180600","display_name":"Relative humidity","level":2,"score":0.35530000925064087},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.35510000586509705},{"id":"https://openalex.org/C1633027","wikidata":"https://www.wikidata.org/wiki/Q815820","display_name":"Computational fluid dynamics","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C2983363897","wikidata":"https://www.wikidata.org/wiki/Q845339","display_name":"Air temperature","level":2,"score":0.3443000018596649},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.34119999408721924},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.3312000036239624},{"id":"https://openalex.org/C200457457","wikidata":"https://www.wikidata.org/wiki/Q584049","display_name":"Ventilation (architecture)","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C118365302","wikidata":"https://www.wikidata.org/wiki/Q4817115","display_name":"Atmospheric model","level":2,"score":0.32580000162124634},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3122999966144562},{"id":"https://openalex.org/C84967980","wikidata":"https://www.wikidata.org/wiki/Q3517831","display_name":"Operative temperature","level":3,"score":0.3109000027179718},{"id":"https://openalex.org/C160331591","wikidata":"https://www.wikidata.org/wiki/Q7075743","display_name":"Occupancy","level":2,"score":0.3052000105381012},{"id":"https://openalex.org/C2986766689","wikidata":"https://www.wikidata.org/wiki/Q676081","display_name":"Energy exchange","level":2,"score":0.2928999960422516},{"id":"https://openalex.org/C500300565","wikidata":"https://www.wikidata.org/wiki/Q925667","display_name":"Computer simulation","level":2,"score":0.2851000130176544},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.28220000863075256},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.26579999923706055},{"id":"https://openalex.org/C2781099182","wikidata":"https://www.wikidata.org/wiki/Q24963825","display_name":"Cooling load","level":3,"score":0.26010000705718994},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1061/jccee5.cpeng-7033","is_oa":false,"landing_page_url":"https://doi.org/10.1061/jccee5.cpeng-7033","pdf_url":null,"source":{"id":"https://openalex.org/S176637136","display_name":"Journal of Computing in Civil Engineering","issn_l":"0887-3801","issn":["0887-3801","1943-5487"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315747","host_organization_name":"American Society of Civil Engineers","host_organization_lineage":["https://openalex.org/P4310315747"],"host_organization_lineage_names":["American Society of Civil Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing in Civil Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.48155084252357483,"display_name":"Climate action","id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1500979280","https://openalex.org/W1510965626","https://openalex.org/W1969258310","https://openalex.org/W1969974566","https://openalex.org/W1994766241","https://openalex.org/W2002687980","https://openalex.org/W2005968543","https://openalex.org/W2013346053","https://openalex.org/W2023944533","https://openalex.org/W2044331609","https://openalex.org/W2044542806","https://openalex.org/W2060843763","https://openalex.org/W2074398030","https://openalex.org/W2078903377","https://openalex.org/W2115746287","https://openalex.org/W2134967905","https://openalex.org/W2170285147","https://openalex.org/W2530165053","https://openalex.org/W2588526596","https://openalex.org/W2604604667","https://openalex.org/W2626726142","https://openalex.org/W2793877845","https://openalex.org/W2888284943","https://openalex.org/W2899283552","https://openalex.org/W2944166938","https://openalex.org/W2971765423","https://openalex.org/W3010640043","https://openalex.org/W3013497865","https://openalex.org/W3040832692","https://openalex.org/W3163487941","https://openalex.org/W4285082063","https://openalex.org/W4294750274","https://openalex.org/W4309047502","https://openalex.org/W4322760659","https://openalex.org/W4323981369","https://openalex.org/W4385691251","https://openalex.org/W4387655444","https://openalex.org/W4388263857","https://openalex.org/W4394717057","https://openalex.org/W4395689606"],"related_works":[],"abstract_inverted_index":{"Outdoor":[0],"microclimate":[1,61],"is":[2],"critical":[3],"in":[4,41,54],"assessing":[5],"thermal":[6],"comfort":[7],"and":[8,28,39,63,73,95,116,175],"building":[9],"energy":[10],"efficiency.":[11,163],"However,":[12],"traditional":[13],"numerical":[14],"simulations":[15],"are":[16],"limited":[17],"by":[18,56],"low":[19],"computational":[20,162],"efficiency":[21],"due":[22],"to":[23,70,156],"their":[24],"large":[25],"model":[26,62,84,89],"scales":[27],"complex":[29,123],"heat-mass":[30],"exchange":[31],"processes.":[32],"Artificial":[33],"neural":[34,67],"networks":[35],"(ANNs),":[36],"leveraging":[37],"rapidity":[38],"accuracy":[40],"high-dimensional":[42],"nonlinear":[43],"mapping,":[44],"offer":[45],"a":[46,52,58,65,82,87],"promising":[47],"solution.":[48],"This":[49,164],"study":[50],"analyzes":[51],"neighborhood":[53],"Guangzhou":[55],"establishing":[57],"three-dimensional":[59],"(3D)":[60],"applying":[64],"deep":[66],"network":[68],"(DNN)":[69],"predict":[71],"temperature":[72,131],"humidity":[74,145],"ratio":[75,146],"distributions.":[76],"We":[77],"compared":[78],"the":[79,103,111,127],"performance":[80],"of":[81,113,126,139],"single-output":[83],"(DNN-S)":[85],"against":[86],"dual-output":[88],"(DNN-D)":[90],"under":[91,148],"both":[92],"two-dimensional":[93],"(2D)":[94],"3D":[96,104],"data":[97],"conditions.":[98],"The":[99,151],"results":[100],"indicate":[101],"that":[102],"DNN-S":[105],"achieved":[106],"superior":[107],"accuracy,":[108],"effectively":[109],"replicating":[110],"effects":[112],"airflow":[114],"inlets":[115],"surface":[117],"influences.":[118],"In":[119],"regions":[120,140],"with":[121],"lower-level":[122],"airflow,":[124],"90.7%":[125],"studied":[128],"area":[129],"exhibited":[130],"prediction":[132,154],"errors":[133,147],"below":[134],"0.5\u00b0C,":[135],"while":[136],"over":[137],"83.2%":[138],"at":[141],"all":[142],"heights":[143],"maintained":[144],"0.3":[149],"g/kg.":[150],"DNN":[152],"reduced":[153],"time":[155],"just":[157],"2":[158],"s,":[159],"significantly":[160],"enhancing":[161],"approach":[165],"provides":[166],"an":[167],"effective":[168],"tool":[169],"for":[170],"urban":[171],"planning,":[172],"climate":[173],"assessment,":[174],"coupled":[176],"simulations,":[177],"demonstrating":[178],"broad":[179],"application":[180],"potential.":[181]},"counts_by_year":[],"updated_date":"2025-11-23T05:13:22.807545","created_date":"2025-11-23T00:00:00"}