{"id":"https://openalex.org/W4312949476","doi":"https://doi.org/10.1109/access.2022.3228441","title":"A Novel Multi-Model Stacking Ensemble Learning Method for Metro Traction Energy Prediction","display_name":"A Novel Multi-Model Stacking Ensemble Learning Method for Metro Traction Energy Prediction","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4312949476","doi":"https://doi.org/10.1109/access.2022.3228441"},"language":"en","primary_location":{"id":"doi:10.1109/access.2022.3228441","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3228441","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09980369.pdf","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://ieeexplore.ieee.org/ielx7/6287639/6514899/09980369.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033415872","display_name":"Shan Lin","orcid":"https://orcid.org/0000-0002-4418-8688"},"institutions":[{"id":"https://openalex.org/I4210145820","display_name":"Guangzhou Metro Group (China)","ror":"https://ror.org/04gfyef21","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210145820"]},{"id":"https://openalex.org/I4387152412","display_name":"Guangzhou Metro Design & Research Institute","ror":"https://ror.org/02sdahq48","country_code":null,"type":"company","lineage":["https://openalex.org/I4387152412"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shan Lin","raw_affiliation_strings":["Guangzhou Metro Design and Research Institute Company Ltd., Guangzhou, China","Guangzhou Metro Design and Research Institute Co., Ltd., Guangzhou, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"Guangzhou Metro Design and Research Institute Company Ltd., Guangzhou, China","institution_ids":["https://openalex.org/I4387152412"]},{"raw_affiliation_string":"Guangzhou Metro Design and Research Institute Co., Ltd., Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I4210145820","https://openalex.org/I4387152412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032381814","display_name":"Xingzhong Nong","orcid":null},"institutions":[{"id":"https://openalex.org/I4210145820","display_name":"Guangzhou Metro Group (China)","ror":"https://ror.org/04gfyef21","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210145820"]},{"id":"https://openalex.org/I4387152412","display_name":"Guangzhou Metro Design & Research Institute","ror":"https://ror.org/02sdahq48","country_code":null,"type":"company","lineage":["https://openalex.org/I4387152412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xingzhong Nong","raw_affiliation_strings":["Guangzhou Metro Design and Research Institute Company Ltd., Guangzhou, China","Guangzhou Metro Design and Research Institute Co., Ltd., Guangzhou, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"Guangzhou Metro Design and Research Institute Company Ltd., Guangzhou, China","institution_ids":["https://openalex.org/I4387152412"]},{"raw_affiliation_string":"Guangzhou Metro Design and Research Institute Co., Ltd., Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I4210145820","https://openalex.org/I4387152412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052740365","display_name":"Jianqiang Luo","orcid":"https://orcid.org/0000-0003-0537-0572"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianqiang Luo","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou, China","School of Automation, Guangdong University of Technology, Guangzhou, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]},{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072271321","display_name":"Chen'en Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen'en Wang","raw_affiliation_strings":["School of Automation, Guangdong University of Technology, Guangzhou, China","School of Automation, Guangdong University of Technology, Guangzhou, Guangdong, China"],"affiliations":[{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I139024713"]},{"raw_affiliation_string":"School of Automation, Guangdong University of Technology, Guangzhou, Guangdong, China","institution_ids":["https://openalex.org/I139024713"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5033415872"],"corresponding_institution_ids":["https://openalex.org/I4210145820","https://openalex.org/I4387152412"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.0824,"has_fulltext":true,"cited_by_count":9,"citation_normalized_percentile":{"value":0.80949536,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"10","issue":null,"first_page":"129231","last_page":"129244"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.9991999864578247,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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":0.9987000226974487,"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/T10842","display_name":"Railway Engineering and Dynamics","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"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/computer-science","display_name":"Computer science","score":0.7506452202796936},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.6385396718978882},{"id":"https://openalex.org/keywords/traction","display_name":"Traction (geology)","score":0.5692650675773621},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5351676940917969},{"id":"https://openalex.org/keywords/stacking","display_name":"Stacking","score":0.5181830525398254},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5013446807861328},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4180072546005249},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41565054655075073},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3964197635650635},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1471158266067505}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7506452202796936},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.6385396718978882},{"id":"https://openalex.org/C38834483","wikidata":"https://www.wikidata.org/wiki/Q17000223","display_name":"Traction (geology)","level":2,"score":0.5692650675773621},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5351676940917969},{"id":"https://openalex.org/C33347731","wikidata":"https://www.wikidata.org/wiki/Q285210","display_name":"Stacking","level":2,"score":0.5181830525398254},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5013446807861328},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4180072546005249},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41565054655075073},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3964197635650635},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1471158266067505},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C46141821","wikidata":"https://www.wikidata.org/wiki/Q209402","display_name":"Nuclear magnetic resonance","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2022.3228441","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3228441","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09980369.pdf","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"},{"id":"pmh:oai:doaj.org/article:3b4705b93779435fb18e8b0759f1878b","is_oa":true,"landing_page_url":"https://doaj.org/article/3b4705b93779435fb18e8b0759f1878b","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 10, Pp 129231-129244 (2022)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2022.3228441","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2022.3228441","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/09980369.pdf","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":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.9200000166893005}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4312949476.pdf","grobid_xml":"https://content.openalex.org/works/W4312949476.grobid-xml"},"referenced_works_count":47,"referenced_works":["https://openalex.org/W1965895201","https://openalex.org/W2063032533","https://openalex.org/W2128731188","https://openalex.org/W2473205972","https://openalex.org/W2529332229","https://openalex.org/W2739748921","https://openalex.org/W2739824434","https://openalex.org/W2782485997","https://openalex.org/W2791006446","https://openalex.org/W2792986592","https://openalex.org/W2884486887","https://openalex.org/W2899657167","https://openalex.org/W2901004617","https://openalex.org/W2902368416","https://openalex.org/W2942231644","https://openalex.org/W2944436518","https://openalex.org/W2947666609","https://openalex.org/W2960560113","https://openalex.org/W2964045355","https://openalex.org/W2964152782","https://openalex.org/W2965492561","https://openalex.org/W2970602317","https://openalex.org/W2981581709","https://openalex.org/W2995621191","https://openalex.org/W3008571545","https://openalex.org/W3036982440","https://openalex.org/W3093310271","https://openalex.org/W3102100346","https://openalex.org/W3108351918","https://openalex.org/W3117298323","https://openalex.org/W3125569183","https://openalex.org/W3151576634","https://openalex.org/W3159843711","https://openalex.org/W3164731060","https://openalex.org/W3174194107","https://openalex.org/W3176900260","https://openalex.org/W3188145474","https://openalex.org/W3201319866","https://openalex.org/W3211177584","https://openalex.org/W3211940428","https://openalex.org/W4207050292","https://openalex.org/W4210790750","https://openalex.org/W4229460339","https://openalex.org/W4282977571","https://openalex.org/W4283750094","https://openalex.org/W4284671606","https://openalex.org/W6741832134"],"related_works":["https://openalex.org/W2035329725","https://openalex.org/W4376641153","https://openalex.org/W2050788868","https://openalex.org/W4250391473","https://openalex.org/W3045075405","https://openalex.org/W4302292679","https://openalex.org/W2956222435","https://openalex.org/W4241625287","https://openalex.org/W4295885776","https://openalex.org/W2031579480"],"abstract_inverted_index":{"Metro":[0,141],"traction":[1,44,80,100,107],"energy":[2,45,81,101,108],"prediction":[3,31,36,40,129,152],"is":[4,47,73,117,135],"the":[5,16,21,35,97,114,120,132,145,148,151],"basis":[6],"of":[7,20,79,106,150],"abnormal":[8],"monitoring":[9],"and":[10,18,58,90,103,144],"plays":[11],"an":[12],"indispensable":[13],"role":[14],"in":[15],"planning":[17],"operation":[19],"metro":[22,43],"system.":[23],"However,":[24],"current":[25],"studies":[26],"rarely":[27],"offer":[28],"a":[29,38,125],"satisfactory":[30],"performance.":[32],"To":[33],"improve":[34],"accuracy,":[37],"novel":[39],"method":[41,134],"for":[42],"consumption":[46,102,109],"proposed":[48,133],"based":[49],"on":[50],"gradient":[51],"penalty":[52],"Wasserstein":[53],"generative":[54],"adversarial":[55],"network":[56],"(WGAN-GP)":[57],"stacking":[59,126],"ensemble":[60,127],"learning":[61,128],"with":[62,137],"multi-model":[63],"integration.":[64],"Firstly,":[65],"aiming":[66],"to":[67,75,94,123],"collect":[68],"effective":[69],"train":[70],"data,":[71],"WGAN-GP":[72],"used":[74],"generate":[76],"characteristic":[77,104],"data":[78,105,138],"consumption.":[82],"Then,":[83],"various":[84],"algorithms":[85],"like":[86],"BP,":[87],"SVM,":[88],"ELM,":[89],"XGBoost":[91,115],"are":[92],"employed":[93],"preliminarily":[95],"disclose":[96],"relationship":[98],"between":[99],"via":[110],"K-fold":[111],"verification.":[112],"Thereafter,":[113],"algorithm":[116],"implemented":[118],"as":[119],"meta":[121],"model":[122],"construct":[124],"model.":[130,153],"Finally,":[131],"verified":[136],"from":[139],"Guangzhou":[140],"Line":[142],"13,":[143],"results":[146],"substantiate":[147],"effectiveness":[149]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}