{"id":"https://openalex.org/W4401415929","doi":"https://doi.org/10.1109/access.2024.3440649","title":"Real-Time Prewarning Method of Subway Turnout Jamming Failure Based on Short-Term Load Prediction and Ensemble LVQ Learning","display_name":"Real-Time Prewarning Method of Subway Turnout Jamming Failure Based on Short-Term Load Prediction and Ensemble LVQ Learning","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4401415929","doi":"https://doi.org/10.1109/access.2024.3440649"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3440649","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3440649","pdf_url":null,"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":null,"license_id":null,"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://doi.org/10.1109/access.2024.3440649","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012209822","display_name":"Hao Wen","orcid":"https://orcid.org/0009-0008-8450-7795"},"institutions":[{"id":"https://openalex.org/I4210162404","display_name":"China Railway Construction Machinery Research & Design Institute","ror":"https://ror.org/05qw55b97","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210162404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wen","raw_affiliation_strings":["School of Rail Communication & Signals and Electrification, Wuhan Railway Vocational College of Technology, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Rail Communication & Signals and Electrification, Wuhan Railway Vocational College of Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I4210162404"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056439477","display_name":"Jie Xiao","orcid":"https://orcid.org/0000-0003-3265-9179"},"institutions":[{"id":"https://openalex.org/I4210162404","display_name":"China Railway Construction Machinery Research & Design Institute","ror":"https://ror.org/05qw55b97","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210162404"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Xiao","raw_affiliation_strings":["School of Rail Communication & Signals and Electrification, Wuhan Railway Vocational College of Technology, Wuhan, Hubei, China"],"raw_orcid":"https://orcid.org/0000-0003-3265-9179","affiliations":[{"raw_affiliation_string":"School of Rail Communication & Signals and Electrification, Wuhan Railway Vocational College of Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I4210162404"]}]},{"author_position":"last","author":{"id":null,"display_name":"Guangxiang Xie","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guangxiang Xie","raw_affiliation_strings":["Wuhan Metro Operation Company Ltd., Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan Metro Operation Company Ltd., Wuhan, Hubei, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.213,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.5086102,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"12","issue":null,"first_page":"109861","last_page":"109876"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9900000095367432,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9900000095367432,"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/T14011","display_name":"Elevator Systems and Control","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T10220","display_name":"Machine Fault Diagnosis Techniques","score":0.9707000255584717,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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":0.7278290390968323},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5410839319229126},{"id":"https://openalex.org/keywords/turnout","display_name":"Turnout","score":0.4767794907093048},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4496774673461914},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4385872483253479},{"id":"https://openalex.org/keywords/jamming","display_name":"Jamming","score":0.42331066727638245},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.41262492537498474},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.33341971039772034},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.14539551734924316}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7278290390968323},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5410839319229126},{"id":"https://openalex.org/C2779838221","wikidata":"https://www.wikidata.org/wiki/Q7856080","display_name":"Turnout","level":4,"score":0.4767794907093048},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4496774673461914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4385872483253479},{"id":"https://openalex.org/C2779079576","wikidata":"https://www.wikidata.org/wiki/Q17092823","display_name":"Jamming","level":2,"score":0.42331066727638245},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.41262492537498474},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.33341971039772034},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.14539551734924316},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3440649","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3440649","pdf_url":null,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2530ac1edc024b3089215a7a2486934f","is_oa":true,"landing_page_url":"https://doaj.org/article/2530ac1edc024b3089215a7a2486934f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 12, Pp 109861-109876 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3440649","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3440649","pdf_url":null,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Climate action","score":0.47999998927116394,"id":"https://metadata.un.org/sdg/13"}],"awards":[{"id":"https://openalex.org/G963546443","display_name":null,"funder_award_id":"B2022527","funder_id":"https://openalex.org/F4320313620","funder_display_name":"Hubei Provincial Department of Education"}],"funders":[{"id":"https://openalex.org/F4320313620","display_name":"Hubei Provincial Department of Education","ror":"https://ror.org/05yaa9j15"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1495282456","https://openalex.org/W2011092307","https://openalex.org/W2079696027","https://openalex.org/W2156742582","https://openalex.org/W2171998198","https://openalex.org/W2325226967","https://openalex.org/W2373108660","https://openalex.org/W2892598691","https://openalex.org/W2923535998","https://openalex.org/W2981680696","https://openalex.org/W3119183696","https://openalex.org/W3136529629","https://openalex.org/W3169880793","https://openalex.org/W3201115733","https://openalex.org/W4225672652","https://openalex.org/W4285095127","https://openalex.org/W4292573073","https://openalex.org/W4308337415","https://openalex.org/W4310696200","https://openalex.org/W4385819837","https://openalex.org/W4387334832"],"related_works":["https://openalex.org/W2044173263","https://openalex.org/W856308142","https://openalex.org/W2373209389","https://openalex.org/W2197796436","https://openalex.org/W2264221613","https://openalex.org/W4246879814","https://openalex.org/W2110286895","https://openalex.org/W1168036533","https://openalex.org/W2372829958","https://openalex.org/W3146111732"],"abstract_inverted_index":{"Turnout":[0],"is":[1,63,77,91,151,171,201,251],"the":[2,7,43,51,81,87,95,99,103,106,110,141,147,154,175,183,194,205,209,223,238,247,255,260],"key":[3],"equipment":[4],"for":[5,73,158,263],"realizing":[6],"turnback":[8],"of":[9,45,54,102,140,186,198,208,241],"subway":[10],"trains.":[11],"Frequent":[12],"movements":[13],"and":[14,36,49,86,109,121,136,161,227],"environmental":[15],"changes":[16,97],"often":[17],"lead":[18],"to":[19,40,79,93,173,181],"abnormal":[20],"increases":[21],"in":[22,28,98,179],"resistance":[23,100],"during":[24,47],"turnout":[25,58],"conversion,":[26],"resulting":[27],"jamming":[29,59,199],"failures":[30],"that":[31],"directly":[32],"affect":[33],"traffic":[34],"safety":[35],"efficiency.":[37],"In":[38],"order":[39,180],"effectively":[41,228],"foresee":[42],"risk":[44,117,142],"failure":[46],"operation":[48],"minimize":[50],"adverse":[52],"effects":[53],"failure,":[55],"a":[56,66,116,122,167],"real-time":[57],"fault":[60,200,242,256],"prewarning":[61,125,148,159,177,224,245,248],"method":[62,220],"proposed.":[64],"Firstly,":[65],"weighted":[67],"grey":[68],"prediction":[69],"machine":[70],"using":[71],"PSO":[72],"weight":[74],"optimization":[75],"(PSO-WGPM)":[76],"proposed":[78,219],"predict":[80],"short-term":[82],"action":[83],"load":[84],"index,":[85],"predicted":[88,107,210],"index":[89,108,112,119,144,211],"series":[90],"used":[92],"characterize":[94],"future":[96],"state":[101],"turnout;":[104],"Secondly,":[105],"generated":[111],"are":[113,131],"combined":[114],"into":[115,153],"identification":[118,143],"series,":[120],"multi-dimensional":[123],"hybrid":[124,168],"feature":[126,149],"set":[127,150],"with":[128,232],"time":[129,196,240,250],"continuity":[130],"constructed":[132],"by":[133],"time-domain":[134],"characteristics":[135,139],"overload":[137,206],"statistical":[138],"series;":[145],"Then,":[146],"fed":[152],"LVQ":[155],"neural":[156],"network":[157],"discrimination,":[160],"an":[162,192],"ensemble":[163],"learning":[164,184],"based":[165,203],"on":[166,204],"voting":[169],"strategy":[170],"designed":[172],"obtain":[174],"final":[176],"result,":[178],"fit":[182],"environment":[185],"unbalanced":[187],"small-scale":[188],"samples;":[189],"After":[190],"giving":[191],"prewarning,":[193],"occurrence":[195],"range":[197,239],"inferred":[202],"rate":[207,226],"series.":[212],"The":[213,218],"experimental":[214],"results":[215],"show":[216],"that:":[217],"can":[221,236],"improve":[222],"success":[225],"control":[229],"false":[230],"alarms,":[231],"good":[233],"correctness;":[234],"it":[235],"infer":[237],"occurrence,":[243],"achieving":[244],"accuracy;":[246],"calculation":[249],"much":[252],"shorter":[253],"than":[254],"advance":[257],"time,":[258],"meeting":[259],"timeliness":[261],"requirements":[262],"applications.":[264]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}