{"id":"https://openalex.org/W2896156853","doi":"https://doi.org/10.1145/3265689.3265712","title":"Forecasting Road Surface Temperature in Beijing Based on Machine Learning Algorithms","display_name":"Forecasting Road Surface Temperature in Beijing Based on Machine Learning Algorithms","publication_year":2018,"publication_date":"2018-07-28","ids":{"openalex":"https://openalex.org/W2896156853","doi":"https://doi.org/10.1145/3265689.3265712","mag":"2896156853"},"language":"en","primary_location":{"id":"doi:10.1145/3265689.3265712","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3265689.3265712","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Conference on Crowd Science and Engineering","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/A5100461634","display_name":"Bo Liu","orcid":"https://orcid.org/0000-0002-2393-117X"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Liu","raw_affiliation_strings":["Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, China and School of Software Engineering, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing, China and School of Software Engineering, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101706257","display_name":"Libin Shen","orcid":"https://orcid.org/0000-0002-7967-0538"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Libin Shen","raw_affiliation_strings":["School of Software Engineering, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073507184","display_name":"Huanling You","orcid":null},"institutions":[{"id":"https://openalex.org/I141301092","display_name":"China Meteorological Administration","ror":"https://ror.org/00bx3rb98","country_code":"CN","type":"government","lineage":["https://openalex.org/I141301092"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huanling You","raw_affiliation_strings":["Institute of Urban Meteorology, China Meteorological Administration, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Urban Meteorology, China Meteorological Administration, Beijing, China","institution_ids":["https://openalex.org/I141301092"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056041589","display_name":"Yan Dong","orcid":"https://orcid.org/0000-0002-9512-6903"},"institutions":[{"id":"https://openalex.org/I4210137516","display_name":"Beijing Meteorological Bureau","ror":"https://ror.org/03wd9vk87","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210137516"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Dong","raw_affiliation_strings":["Beijing Meteorological Service Center, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Meteorological Service Center, Beijing, China","institution_ids":["https://openalex.org/I4210137516"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100393880","display_name":"Jianqiang Li","orcid":"https://orcid.org/0000-0003-1995-9249"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianqiang Li","raw_affiliation_strings":["School of Software Engineering, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100355277","display_name":"Yong Li","orcid":"https://orcid.org/0000-0001-5617-1659"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Li","raw_affiliation_strings":["School of Software Engineering, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Software Engineering, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041965081","display_name":"Jianlei Lang","orcid":"https://orcid.org/0000-0001-5575-0018"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianlei Lang","raw_affiliation_strings":["Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing, China and College of Environmental &amp; Energy Engineering, Beijing University of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Beijing on Regional Air Pollution Control, Beijing University of Technology, Beijing, China and College of Environmental &amp; Energy Engineering, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091039444","display_name":"Rentao Gu","orcid":"https://orcid.org/0000-0003-3183-2857"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rentao Gu","raw_affiliation_strings":["Beijing Laboratory of Advanced Information Networks, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Laboratory of Advanced Information Networks, School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12682","display_name":"Smart Materials for Construction","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"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/T12682","display_name":"Smart Materials for Construction","score":0.9987999796867371,"subfield":{"id":"https://openalex.org/subfields/2310","display_name":"Pollution"},"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9779000282287598,"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/T13955","display_name":"Evaluation Methods in Various Fields","score":0.9545000195503235,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"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/random-forest","display_name":"Random forest","score":0.813652753829956},{"id":"https://openalex.org/keywords/beijing","display_name":"Beijing","score":0.7745668888092041},{"id":"https://openalex.org/keywords/lasso","display_name":"Lasso (programming language)","score":0.7127574682235718},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6592984795570374},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.6422482132911682},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6149426698684692},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.6046057343482971},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5973870158195496},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5919508337974548},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.5006086826324463},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.4567881226539612},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.16762837767601013},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09025931358337402}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.813652753829956},{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.7745668888092041},{"id":"https://openalex.org/C37616216","wikidata":"https://www.wikidata.org/wiki/Q3218363","display_name":"Lasso (programming language)","level":2,"score":0.7127574682235718},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6592984795570374},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.6422482132911682},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6149426698684692},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.6046057343482971},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5973870158195496},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5919508337974548},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.5006086826324463},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.4567881226539612},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.16762837767601013},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09025931358337402},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3265689.3265712","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3265689.3265712","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 3rd International Conference on Crowd Science and Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5099999904632568,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W852276632","https://openalex.org/W1678356000","https://openalex.org/W1989365837","https://openalex.org/W2033990175","https://openalex.org/W2113815821","https://openalex.org/W2119862467","https://openalex.org/W2135046866","https://openalex.org/W2135293965","https://openalex.org/W2783116631","https://openalex.org/W2790718085","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W4255828509","https://openalex.org/W6658784473","https://openalex.org/W6813791379"],"related_works":["https://openalex.org/W2967733078","https://openalex.org/W3204430031","https://openalex.org/W3137904399","https://openalex.org/W4310492845","https://openalex.org/W2885778889","https://openalex.org/W4310224730","https://openalex.org/W2766514146","https://openalex.org/W4289703016","https://openalex.org/W2885516856","https://openalex.org/W4296079469"],"abstract_inverted_index":{"With":[0],"the":[1,12,24,44,51,80,95,109],"influence":[2],"of":[3,14,47,97],"extreme":[4],"weather,":[5],"road":[6],"surface":[7],"temperature":[8],"(RST),":[9],"which":[10],"threatens":[11],"safety":[13],"people's":[15],"travel,":[16],"has":[17],"attracted":[18],"more":[19,21],"and":[20,26,49,66,73,83,92,111],"attention":[22],"to":[23,33,42],"government":[25],"citizens.":[27],"However,":[28],"traditional":[29],"methods":[30],"are":[31],"hard":[32],"meet":[34,50],"real-time":[35,52],"requirements":[36],"in":[37],"forecasting":[38],"RST.":[39],"In":[40],"order":[41],"improve":[43],"predictive":[45],"accuracy":[46],"RST":[48,81],"requirement,":[53],"this":[54],"paper":[55],"compares":[56],"three":[57,98],"different":[58],"machine":[59],"learning":[60],"algorithms":[61],"including,":[62],"Least":[63],"Absolute":[64],"Shrinkage":[65],"Selection":[67],"Operator":[68],"(LASSO),":[69],"Random":[70],"Forest":[71],"(RF)":[72],"Gradient":[74],"Boosting":[75],"Regression":[76],"Tree":[77],"(GBRT).":[78],"Using":[79],"data":[82,88],"BJ-RUC":[84],"(Beijing-rapidly":[85],"update":[86],"cycle)":[87],"during":[89],"November":[90],"2012":[91],"June":[93],"2015,":[94],"performance":[96],"models":[99],"is":[100,114],"evaluated.":[101],"The":[102],"experimental":[103],"results":[104],"show":[105],"that":[106],"GBRT":[107],"performs":[108],"best":[110],"its":[112],"MSE":[113],"6.7853.":[115]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
