{"id":"https://openalex.org/W4414032258","doi":"https://doi.org/10.1142/s1752890925500205","title":"Forecasting Residential Property Prices in Jiaxing City, China: A Hybrid Machine Learning Framework Integrating Gaussian Process Regressions and Bayesian Optimization","display_name":"Forecasting Residential Property Prices in Jiaxing City, China: A Hybrid Machine Learning Framework Integrating Gaussian Process Regressions and Bayesian Optimization","publication_year":2025,"publication_date":"2025-09-06","ids":{"openalex":"https://openalex.org/W4414032258","doi":"https://doi.org/10.1142/s1752890925500205"},"language":"en","primary_location":{"id":"doi:10.1142/s1752890925500205","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1752890925500205","pdf_url":null,"source":{"id":"https://openalex.org/S4210199942","display_name":"Journal of Uncertain Systems","issn_l":"1752-8909","issn":["1752-8909","1752-8917"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Uncertain Systems","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":"https://openalex.org/A5054390461","display_name":"Bingzi Jin","orcid":"https://orcid.org/0009-0005-1620-7772"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bingzi Jin","raw_affiliation_strings":["Advanced Micro Devices (China) Co., Ltd., Shanghai, P. R. China"],"raw_orcid":"https://orcid.org/0009-0005-1620-7772","affiliations":[{"raw_affiliation_string":"Advanced Micro Devices (China) Co., Ltd., Shanghai, P. R. China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019106763","display_name":"Xiaojie Xu","orcid":"https://orcid.org/0000-0002-4452-1540"},"institutions":[{"id":"https://openalex.org/I137902535","display_name":"North Carolina State University","ror":"https://ror.org/04tj63d06","country_code":"US","type":"education","lineage":["https://openalex.org/I137902535"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaojie Xu","raw_affiliation_strings":["North Carolina State University, Raleigh, NC, 27695, USA"],"raw_orcid":"https://orcid.org/0000-0002-4452-1540","affiliations":[{"raw_affiliation_string":"North Carolina State University, Raleigh, NC, 27695, USA","institution_ids":["https://openalex.org/I137902535"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5054390461"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.0902,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.94254112,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":"19","issue":"02","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11052","display_name":"Energy Load and Power Forecasting","score":0.7299000024795532,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.7299000024795532,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.6769999861717224,"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.6398000121116638,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.6330793499946594},{"id":"https://openalex.org/keywords/property","display_name":"Property (philosophy)","score":0.6219522356987},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.606792688369751},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6041927337646484},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5639139413833618},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.5278601050376892},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4983344078063965},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.47988712787628174},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47434818744659424},{"id":"https://openalex.org/keywords/bayesian-optimization","display_name":"Bayesian optimization","score":0.4686149060726166},{"id":"https://openalex.org/keywords/china","display_name":"China","score":0.42972102761268616},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.39145728945732117},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2635268568992615},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.16399627923965454},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.06129050254821777}],"concepts":[{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.6330793499946594},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.6219522356987},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.606792688369751},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6041927337646484},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5639139413833618},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.5278601050376892},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4983344078063965},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.47988712787628174},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47434818744659424},{"id":"https://openalex.org/C2778049539","wikidata":"https://www.wikidata.org/wiki/Q17002908","display_name":"Bayesian optimization","level":2,"score":0.4686149060726166},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.42972102761268616},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.39145728945732117},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2635268568992615},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.16399627923965454},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.06129050254821777},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C147597530","wikidata":"https://www.wikidata.org/wiki/Q369472","display_name":"Computational chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s1752890925500205","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s1752890925500205","pdf_url":null,"source":{"id":"https://openalex.org/S4210199942","display_name":"Journal of Uncertain Systems","issn_l":"1752-8909","issn":["1752-8909","1752-8917"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Uncertain Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1507259579","https://openalex.org/W1572192998","https://openalex.org/W1816516507","https://openalex.org/W1967666196","https://openalex.org/W1974318113","https://openalex.org/W1996982845","https://openalex.org/W2049049074","https://openalex.org/W2071613476","https://openalex.org/W2077520869","https://openalex.org/W2097966207","https://openalex.org/W2135998982","https://openalex.org/W2143266849","https://openalex.org/W2145455907","https://openalex.org/W2224592433","https://openalex.org/W2555070823","https://openalex.org/W2788973069","https://openalex.org/W2894295805","https://openalex.org/W2902722330","https://openalex.org/W2951282667","https://openalex.org/W2996464143","https://openalex.org/W3004756438","https://openalex.org/W3013314195","https://openalex.org/W3023884729","https://openalex.org/W3032426652","https://openalex.org/W3044141776","https://openalex.org/W3084322042","https://openalex.org/W3108120608","https://openalex.org/W3112071392","https://openalex.org/W3122307655","https://openalex.org/W3122471741","https://openalex.org/W3134319253","https://openalex.org/W3139741344","https://openalex.org/W4292560128","https://openalex.org/W4292560156","https://openalex.org/W4385067866","https://openalex.org/W4398243663","https://openalex.org/W4400986690","https://openalex.org/W4402521902","https://openalex.org/W4404970178","https://openalex.org/W4405476207","https://openalex.org/W4407240089","https://openalex.org/W4407390518"],"related_works":["https://openalex.org/W3104422856","https://openalex.org/W4206864338","https://openalex.org/W4287867179","https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4293503520","https://openalex.org/W4300066510","https://openalex.org/W4406204722","https://openalex.org/W2056958800","https://openalex.org/W4210726438"],"abstract_inverted_index":{"China\u2019s":[0],"property":[1,70],"market":[2,127],"underwent":[3],"a":[4,15,78,110],"period":[5],"of":[6,117,124],"rapid":[7],"growth":[8],"during":[9],"the":[10],"past":[11],"decade,":[12],"followed":[13],"by":[14,26,109],"significant":[16],"downturn":[17],"commencing":[18],"in":[19,34,68,102,140],"late":[20],"2021.":[21],"These":[22],"systemic":[23],"shifts,":[24],"prompted":[25],"changing":[27],"macroeconomic":[28],"landscapes,":[29],"have":[30],"introduced":[31],"considerable":[32],"complexities":[33],"predicting":[35],"real":[36],"estate":[37],"valuations":[38],"for":[39,133],"regulatory":[40],"institutions":[41],"and":[42,61,95],"industry":[43],"participants.":[44],"To":[45],"mitigate":[46],"these":[47],"methodological":[48],"limitations,":[49],"this":[50],"research":[51],"employs":[52],"Gaussian":[53],"Process":[54],"Regression":[55],"(GPR)":[56],"incorporating":[57],"diverse":[58],"kernel":[59],"configurations":[60],"basis":[62],"functions":[63],"to":[64,84],"examine":[65],"monthly":[66],"fluctuations":[67],"residential":[69],"values":[71],"within":[72],"Jiaxing":[73],"City,":[74],"Zhejiang":[75],"Province,":[76],"utilizing":[77],"comprehensive":[79],"dataset":[80],"covering":[81],"October":[82],"2011":[83],"July":[85],"2024.":[86],"The":[87,119],"framework":[88],"was":[89],"enhanced":[90],"through":[91],"Bayesian":[92],"hyperparameter":[93],"optimization":[94],"cross-validation":[96],"techniques,":[97],"demonstrating":[98],"robust":[99],"predictive":[100,144],"accuracy":[101],"out-of-sample":[103],"evaluations":[104],"(January":[105],"2022\u2013July":[106],"2024),":[107],"evidenced":[108],"Relative":[111],"Root":[112],"Mean":[113],"Square":[114],"Error":[115],"(RRMSE)":[116],"0.2523%.":[118],"results":[120],"advance":[121],"theoretical":[122],"understanding":[123],"urban":[125],"housing":[126],"mechanisms":[128],"while":[129],"offering":[130],"practical":[131],"implications":[132],"policy":[134],"formulation,":[135],"whether":[136],"implemented":[137],"autonomously":[138],"or":[139],"conjunction":[141],"with":[142],"supplementary":[143],"approaches.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}
