{"id":"https://openalex.org/W4403676353","doi":"https://doi.org/10.1109/case59546.2024.10711730","title":"Double Deep Q-learning Based on Personalized Thermal Comfort Model for HVAC Optimization","display_name":"Double Deep Q-learning Based on Personalized Thermal Comfort Model for HVAC Optimization","publication_year":2024,"publication_date":"2024-08-28","ids":{"openalex":"https://openalex.org/W4403676353","doi":"https://doi.org/10.1109/case59546.2024.10711730"},"language":"en","primary_location":{"id":"doi:10.1109/case59546.2024.10711730","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/case59546.2024.10711730","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"},"type":"conference-paper","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":"https://openalex.org/A5101058173","display_name":"Hanchen Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanchen Zhou","raw_affiliation_strings":["Tsinghua University,CFINS,Department of Automation,Beijing,China,100084"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,CFINS,Department of Automation,Beijing,China,100084","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115596654","display_name":"Di Wang","orcid":"https://orcid.org/0000-0002-0050-612X"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Wang","raw_affiliation_strings":["Institute of Xi&#x2019;an Jiaotong University,Moe Klinns Lab and Systems Engineering,Xi&#x2019;an,China,710049"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Xi&#x2019;an Jiaotong University,Moe Klinns Lab and Systems Engineering,Xi&#x2019;an,China,710049","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067277859","display_name":"Zhanbo Xu","orcid":"https://orcid.org/0000-0002-8364-0753"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhanbo Xu","raw_affiliation_strings":["Institute of Xi&#x2019;an Jiaotong University,Moe Klinns Lab and Systems Engineering,Xi&#x2019;an,China,710049"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Xi&#x2019;an Jiaotong University,Moe Klinns Lab and Systems Engineering,Xi&#x2019;an,China,710049","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044965133","display_name":"Qing\u2010Shan Jia","orcid":"https://orcid.org/0000-0002-4683-7215"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing-Shan Jia","raw_affiliation_strings":["Tsinghua University,CFINS,Department of Automation,Beijing,China,100084"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua University,CFINS,Department of Automation,Beijing,China,100084","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":0.32801014,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3262","last_page":"3267"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10121","display_name":"Building Energy and Comfort Optimization","score":0.9447000026702881,"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"}},"topics":[{"id":"https://openalex.org/T10121","display_name":"Building Energy and Comfort Optimization","score":0.9447000026702881,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hvac","display_name":"HVAC","score":0.8176359534263611},{"id":"https://openalex.org/keywords/thermal-comfort","display_name":"Thermal comfort","score":0.7100081443786621},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6100481152534485},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5059341788291931},{"id":"https://openalex.org/keywords/computer-architecture","display_name":"Computer architecture","score":0.4073251187801361},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3504020571708679},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.3404526710510254},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.23464205861091614},{"id":"https://openalex.org/keywords/air-conditioning","display_name":"Air conditioning","score":0.17984628677368164},{"id":"https://openalex.org/keywords/mechanical-engineering","display_name":"Mechanical engineering","score":0.15083593130111694},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07782378792762756},{"id":"https://openalex.org/keywords/meteorology","display_name":"Meteorology","score":0.06933540105819702}],"concepts":[{"id":"https://openalex.org/C122346748","wikidata":"https://www.wikidata.org/wiki/Q1798773","display_name":"HVAC","level":3,"score":0.8176359534263611},{"id":"https://openalex.org/C133913538","wikidata":"https://www.wikidata.org/wiki/Q774514","display_name":"Thermal comfort","level":2,"score":0.7100081443786621},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6100481152534485},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5059341788291931},{"id":"https://openalex.org/C118524514","wikidata":"https://www.wikidata.org/wiki/Q173212","display_name":"Computer architecture","level":1,"score":0.4073251187801361},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3504020571708679},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.3404526710510254},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.23464205861091614},{"id":"https://openalex.org/C103742991","wikidata":"https://www.wikidata.org/wiki/Q173725","display_name":"Air conditioning","level":2,"score":0.17984628677368164},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.15083593130111694},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07782378792762756},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.06933540105819702}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/case59546.2024.10711730","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/case59546.2024.10711730","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.7799999713897705}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1667199472","https://openalex.org/W1972971274","https://openalex.org/W2000041175","https://openalex.org/W2000155699","https://openalex.org/W2041225166","https://openalex.org/W2044486831","https://openalex.org/W2071568513","https://openalex.org/W2087551849","https://openalex.org/W2094176506","https://openalex.org/W2329354063","https://openalex.org/W2625874945","https://openalex.org/W2735852439","https://openalex.org/W2801052353","https://openalex.org/W3017236665","https://openalex.org/W3090789943","https://openalex.org/W3129161218","https://openalex.org/W3203740455","https://openalex.org/W4225917661","https://openalex.org/W4392309410","https://openalex.org/W6738867361","https://openalex.org/W6904910827","https://openalex.org/W6987572474"],"related_works":["https://openalex.org/W2112866972","https://openalex.org/W4240233711","https://openalex.org/W2900606913","https://openalex.org/W4320003279","https://openalex.org/W2357294886","https://openalex.org/W3038059713","https://openalex.org/W4281749375","https://openalex.org/W2079922090","https://openalex.org/W2017084161","https://openalex.org/W4388647520"],"abstract_inverted_index":{"The":[0,40],"operation":[1],"of":[2,33,50,110,151,188,200],"Heating,":[3],"Ventilation":[4],"and":[5,16,30,61,83,108,141,192,202,217],"AirConditioning":[6],"(HVAC)":[7],"systems":[8],"in":[9,79,129],"buildings":[10],"has":[11,89],"huge":[12],"energy":[13,28,67,106,215],"saving":[14],"potential":[15],"therefore":[17],"HVAC":[18,87,123,164],"optimization":[19,68,172],"can":[20,213],"greatly":[21],"reduce":[22],"carbon":[23],"emission.":[24],"How":[25],"to":[26,37,45,57,103,137,169,181,196],"balance":[27],"cost":[29],"thermal":[31,59,99,139,155,218],"comfort":[32,100],"occupants":[34],"still":[35],"needs":[36],"be":[38],"researched.":[39],"most":[41],"common":[42],"approach":[43],"is":[44,101,127,135,143,179],"use":[46],"a":[47],"static":[48],"range":[49],"air":[51],"temperature":[52],"or":[53],"PMV(Predicted":[54],"Mean":[55],"Vote)":[56],"describe":[58,138],"sensation":[60],"regard":[62],"it":[63,142],"as":[64],"constraints":[65],"for":[66,122],"problem.":[69,173,184],"However,":[70],"further":[71,104],"research":[72],"illustrates":[73],"that":[74,210],"people":[75],"may":[76],"perceive":[77],"differently":[78],"the":[80,97,171,183,198,221],"same":[81,222],"environment,":[82],"its":[84],"effect":[85],"on":[86,117],"control":[88,204],"not":[90],"been":[91],"analysed.":[92],"To":[93],"address":[94],"this":[95,130],"problem,":[96],"personalized":[98],"considered":[102],"improve":[105],"efficiency":[107,216],"satisfaction":[109,219],"occupants.":[111,152],"Specifically,":[112],"Double":[113,175],"Deep":[114,176],"Q-learning":[115,177],"based":[116],"Personalized":[118],"Thermal":[119],"Comfort":[120],"model":[121],"optimization(called":[124],"PTCDDQ":[125,201,211],"framework)":[126],"proposed":[128],"work.":[131],"First,":[132],"metabolic":[133,159],"rate":[134],"used":[136],"difference,":[140],"estimated":[144],"by":[145,167],"genetic":[146],"algorithm":[147,178],"using":[148],"actual":[149],"votes":[150],"Second,":[153],"PMV":[154],"models":[156,165],"with":[157,163],"different":[158],"rates":[160],"are":[161,194],"combined":[162],"simulated":[166],"Energyplus":[168],"formulate":[170],"Then":[174],"applied":[180],"solve":[182],"Third,":[185],"three":[186],"kinds":[187],"people,":[189],"coldintolerant,":[190],"neutral":[191],"hot-intolerant":[193],"defined":[195],"compare":[197],"performance":[199],"traditional":[203],"methods.":[205],"Case":[206],"study":[207],"results":[208],"show":[209],"framework":[212],"enhance":[214],"at":[220],"time.":[223]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
