{"id":"https://openalex.org/W4281686451","doi":"https://doi.org/10.1093/tse/tdac007","title":"Machine identification method of subway service quality based on smart card data","display_name":"Machine identification method of subway service quality based on smart card data","publication_year":2022,"publication_date":"2022-06-01","ids":{"openalex":"https://openalex.org/W4281686451","doi":"https://doi.org/10.1093/tse/tdac007"},"language":"en","primary_location":{"id":"doi:10.1093/tse/tdac007","doi":"https://doi.org/10.1093/tse/tdac007","is_oa":true,"landing_page_url":"https://doi.org/10.1093/tse/tdac007","pdf_url":null,"source":{"id":"https://openalex.org/S4210220334","display_name":"Transportation Safety and Environment","issn_l":"2631-4428","issn":["2631-4428"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-c","norway-1","poland-20","russia-white-list-1"],"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transportation Safety and Environment","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1093/tse/tdac007","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101712216","display_name":"Maosheng Li","orcid":"https://orcid.org/0000-0003-2799-4490","observed_orcids":["https://orcid.org/0000-0003-2799-4490"]},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Maosheng Li","raw_affiliation_strings":["Rail\u00a0Data\u00a0Research\u00a0and\u00a0Application\u00a0Key\u00a0Laboratory\u00a0of\u00a0Hunan\u00a0Province, Central\u00a0South\u00a0University , Changsha 410075, Hunan, China","School of Traffic and Transportation Engineering, Central South University , Changsha 410075 , \u00a0Hunan, China"],"raw_orcid":"https://orcid.org/0000-0003-2799-4490","affiliations":[{"raw_affiliation_string":"Rail\u00a0Data\u00a0Research\u00a0and\u00a0Application\u00a0Key\u00a0Laboratory\u00a0of\u00a0Hunan\u00a0Province, Central\u00a0South\u00a0University , Changsha 410075, Hunan, China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"School of Traffic and Transportation Engineering, Central South University , Changsha 410075 , \u00a0Hunan, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037716847","display_name":"Ci Tu","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ci Tu","raw_affiliation_strings":["Rail\u00a0Data\u00a0Research\u00a0and\u00a0Application\u00a0Key\u00a0Laboratory\u00a0of\u00a0Hunan\u00a0Province, Central\u00a0South\u00a0University , Changsha 410075, Hunan, China","School of Traffic and Transportation Engineering, Central South University , Changsha 410075 , \u00a0Hunan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rail\u00a0Data\u00a0Research\u00a0and\u00a0Application\u00a0Key\u00a0Laboratory\u00a0of\u00a0Hunan\u00a0Province, Central\u00a0South\u00a0University , Changsha 410075, Hunan, China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"School of Traffic and Transportation Engineering, Central South University , Changsha 410075 , \u00a0Hunan, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100383517","display_name":"Pu Wang","orcid":"https://orcid.org/0000-0002-4503-6643","observed_orcids":["https://orcid.org/0000-0002-4503-6643"]},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pu Wang","raw_affiliation_strings":["Rail\u00a0Data\u00a0Research\u00a0and\u00a0Application\u00a0Key\u00a0Laboratory\u00a0of\u00a0Hunan\u00a0Province, Central\u00a0South\u00a0University , Changsha 410075, Hunan, China","School of Traffic and Transportation Engineering, Central South University , Changsha 410075 , \u00a0Hunan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Rail\u00a0Data\u00a0Research\u00a0and\u00a0Application\u00a0Key\u00a0Laboratory\u00a0of\u00a0Hunan\u00a0Province, Central\u00a0South\u00a0University , Changsha 410075, Hunan, China","institution_ids":["https://openalex.org/I139660479"]},{"raw_affiliation_string":"School of Traffic and Transportation Engineering, Central South University , Changsha 410075 , \u00a0Hunan, China","institution_ids":["https://openalex.org/I139660479"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5101712216"],"corresponding_institution_ids":["https://openalex.org/I139660479"],"apc_list":{"value":0,"currency":"USD","value_usd":0},"apc_paid":{"value":0,"currency":"USD","value_usd":0},"fwci":0.2225,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.4605859,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":93},"biblio":{"volume":"4","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9545999765396118,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10698","display_name":"Transportation Planning and Optimization","score":0.9545999765396118,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.035999998450279236,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.003800000064074993,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/smart-card-data","display_name":"smart card data","score":0.8870000243186951},{"id":"https://openalex.org/keywords/travel-time-distribution","display_name":"travel time distribution","score":0.8700000047683716},{"id":"https://openalex.org/keywords/k-means-clustering","display_name":"K-means clustering","score":0.8450000286102295},{"id":"https://openalex.org/keywords/passenger-travel-behavior","display_name":"passenger travel behavior","score":0.6309999823570251},{"id":"https://openalex.org/keywords/shenzhen-metro","display_name":"Shenzhen Metro","score":0.7429999709129333}],"concepts":[{"id":"https://openalex.org/C140781008","wikidata":"https://www.wikidata.org/wiki/Q1221081","display_name":"Service quality","level":3,"score":0.6482502222061157},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.6135825514793396},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5941769480705261},{"id":"https://openalex.org/C2776962539","wikidata":"https://www.wikidata.org/wiki/Q6472078","display_name":"Lagging","level":2,"score":0.5414469838142395},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5409953594207764},{"id":"https://openalex.org/C110406131","wikidata":"https://www.wikidata.org/wiki/Q41349","display_name":"Smart card","level":2,"score":0.5259416699409485},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5004162788391113},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.48390063643455505},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.4765779972076416},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4129934012889862},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3088400959968567},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1715957522392273},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.13910514116287231},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08321872353553772},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","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},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C136264566","wikidata":"https://www.wikidata.org/wiki/Q159810","display_name":"Economy","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1093/tse/tdac007","doi":"https://doi.org/10.1093/tse/tdac007","is_oa":true,"landing_page_url":"https://doi.org/10.1093/tse/tdac007","pdf_url":null,"source":{"id":"https://openalex.org/S4210220334","display_name":"Transportation Safety and Environment","issn_l":"2631-4428","issn":["2631-4428"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-c","norway-1","poland-20","russia-white-list-1"],"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transportation Safety and Environment","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1093/tse/tdac007","doi":"https://doi.org/10.1093/tse/tdac007","is_oa":true,"landing_page_url":"https://doi.org/10.1093/tse/tdac007","pdf_url":null,"source":{"id":"https://openalex.org/S4210220334","display_name":"Transportation Safety and Environment","issn_l":"2631-4428","issn":["2631-4428"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","dongbi-c","norway-1","poland-20","russia-white-list-1"],"host_organization":"https://openalex.org/P4310311648","host_organization_name":"Oxford University Press","host_organization_lineage":["https://openalex.org/P4310311648","https://openalex.org/P4310311647"],"host_organization_lineage_names":["Oxford University Press","University of Oxford"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Transportation Safety and Environment","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":1.0,"display_name":"Sustainable cities and communities"},{"id":"https://metadata.un.org/sdg/9","score":0.7207000255584717,"display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W814609241","https://openalex.org/W1984650311","https://openalex.org/W2000031724","https://openalex.org/W2022781565","https://openalex.org/W2040162822","https://openalex.org/W2065846791","https://openalex.org/W2080299575","https://openalex.org/W2080833703","https://openalex.org/W2091814890","https://openalex.org/W2127218421","https://openalex.org/W2162503628","https://openalex.org/W2189625117","https://openalex.org/W2299467264","https://openalex.org/W2375616234","https://openalex.org/W2544443587","https://openalex.org/W2557286829","https://openalex.org/W2587183398","https://openalex.org/W3119652684","https://openalex.org/W4255375128","https://openalex.org/W6686980507"],"related_works":["https://openalex.org/W1904954910","https://openalex.org/W2119073741","https://openalex.org/W2057958207","https://openalex.org/W2126268803","https://openalex.org/W814609241","https://openalex.org/W1818126648","https://openalex.org/W1840778708","https://openalex.org/W4313549749","https://openalex.org/W2604537950","https://openalex.org/W2900350637"],"abstract_inverted_index":{"Abstract":[0],"A":[1,164],"new":[2,147,165],"automatic":[3],"evaluation":[4,40,48,68,149],"method":[5,134,150,168,189,221],"of":[6,33,44,113,122,131,151,201,205,214,225],"subway":[7,28,152,217,230],"service":[8,67,102,111,153,179,212,226],"quality":[9,103,112,154],"based":[10,169],"on":[11,170],"metro":[12,116,139],"smart":[13,140],"card":[14,141],"data":[15,142],"is":[16,91,106,155,174],"proposed":[17,107,133,175,183],"suitable":[18,156],"for":[19,55,66,157,176,228],"three":[20],"different":[21,56,74,86,197,203,211],"levels:":[22],"station":[23,60],"pair,":[24],"railway":[25],"line":[26],"and":[27,38,70,97,124,129,159],"network,":[29],"which":[30],"has":[31],"merits":[32],"overcoming":[34],"the":[35,42,80,85,89,101,110,114,119,127,132,178,186,202,215],"previous":[36],"lagging":[37],"subjective":[39],"in":[41,59,76],"system":[43],"\u2018questionnaire":[45],"survey":[46],"plus":[47],"method\u2019.":[49],"First,":[50],"passengers'":[51],"travel":[52,171,193,207],"time":[53,172,194,208],"distribution":[54,173,195,209],"operating":[57,82],"periods":[58],"OD":[61],"pairs":[62],"are":[63,71,135],"introduced":[64],"initially":[65],"purposes":[69],"classified":[72],"into":[73,196],"groups":[75],"order":[77],"to":[78,108,190],"infer":[79],"station's":[81],"characteristics":[83],"at":[84],"periods.":[87],"Second,":[88],"classification":[90],"verified":[92,136],"by":[93,137],"K-means":[94,187],"cluster":[95],"analysis":[96],"K-S":[98],"tests.":[99],"Third,":[100],"weight":[104],"indicator":[105],"identify":[109],"entire":[115],"network":[117],"from":[118],"dual":[120],"perspectives":[121],"passengers":[123],"companies.":[125],"Finally,":[126],"feasibility":[128],"rationality":[130],"Shenzhen":[138],"as":[143],"an":[144],"example.":[145],"The":[146,182,220],"automated":[148],"online":[158],"offline":[160],"application.":[161],"Highlights":[162],"\u2022":[163,181,199,219],"machine":[166],"identification":[167,224],"estimating":[177],"quality.":[180],"model":[184],"employs":[185],"clustering":[188],"distinguish":[191],"passenger's":[192],"modes.":[198],"Characteristics":[200],"modes":[204],"passenger":[206],"reflect":[210],"levels":[213,227],"urban":[216,229],"system.":[218],"provides":[222],"automatically":[223],"operations.":[231]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2022-06-13T00:00:00"}