{"id":"https://openalex.org/W4206338598","doi":"https://doi.org/10.1109/tits.2022.3140386","title":"Enhancing the Understanding of Train Delays With Delay Evolution Pattern Discovery: A Clustering and Bayesian Network Approach","display_name":"Enhancing the Understanding of Train Delays With Delay Evolution Pattern Discovery: A Clustering and Bayesian Network Approach","publication_year":2022,"publication_date":"2022-01-19","ids":{"openalex":"https://openalex.org/W4206338598","doi":"https://doi.org/10.1109/tits.2022.3140386"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2022.3140386","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3140386","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Intelligent Transportation 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/A5055228901","display_name":"Ping Huang","orcid":"https://orcid.org/0000-0002-2794-0188"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]},{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CH","CN"],"is_corresponding":true,"raw_author_name":"Ping Huang","raw_affiliation_strings":["Institute for Transport Planning and Systems, ETH Zurich, Zurich, Switzerland","National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Institute for Transport Planning and Systems, ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]},{"raw_affiliation_string":"National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042206616","display_name":"Thomas Spanninger","orcid":"https://orcid.org/0000-0002-8478-8047"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Thomas Spanninger","raw_affiliation_strings":["Institute for Transport Planning and Systems, ETH Zurich, Zurich, Switzerland"],"affiliations":[{"raw_affiliation_string":"Institute for Transport Planning and Systems, ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035480904","display_name":"Francesco Corman","orcid":"https://orcid.org/0000-0002-6036-5832"},"institutions":[{"id":"https://openalex.org/I35440088","display_name":"ETH Zurich","ror":"https://ror.org/05a28rw58","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I35440088"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Francesco Corman","raw_affiliation_strings":["Institute for Transport Planning and Systems, ETH Zurich, Zurich, Switzerland"],"affiliations":[{"raw_affiliation_string":"Institute for Transport Planning and Systems, ETH Zurich, Zurich, Switzerland","institution_ids":["https://openalex.org/I35440088"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5055228901"],"corresponding_institution_ids":["https://openalex.org/I35440088","https://openalex.org/I4800084"],"apc_list":null,"apc_paid":null,"fwci":6.2193,"has_fulltext":false,"cited_by_count":47,"citation_normalized_percentile":{"value":0.96603601,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"23","issue":"9","first_page":"15367","last_page":"15381"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.9962999820709229,"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":0.9962999820709229,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9858999848365784,"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/T10842","display_name":"Railway Engineering and Dynamics","score":0.9751999974250793,"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/cluster-analysis","display_name":"Cluster analysis","score":0.7913482785224915},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.680757999420166},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5563153028488159},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5428363084793091},{"id":"https://openalex.org/keywords/dynamic-bayesian-network","display_name":"Dynamic Bayesian network","score":0.5369875431060791},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.4995107650756836},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4801889657974243},{"id":"https://openalex.org/keywords/network-delay","display_name":"Network delay","score":0.4455573558807373},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4455040991306305},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4199959337711334},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4087263345718384}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7913482785224915},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.680757999420166},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5563153028488159},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5428363084793091},{"id":"https://openalex.org/C82142266","wikidata":"https://www.wikidata.org/wiki/Q3456604","display_name":"Dynamic Bayesian network","level":3,"score":0.5369875431060791},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.4995107650756836},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4801889657974243},{"id":"https://openalex.org/C152623178","wikidata":"https://www.wikidata.org/wiki/Q436417","display_name":"Network delay","level":3,"score":0.4455573558807373},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4455040991306305},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4199959337711334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4087263345718384},{"id":"https://openalex.org/C158379750","wikidata":"https://www.wikidata.org/wiki/Q214111","display_name":"Network packet","level":2,"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/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2022.3140386","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2022.3140386","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Intelligent Transportation 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":58,"referenced_works":["https://openalex.org/W1755360231","https://openalex.org/W1964357740","https://openalex.org/W1972440649","https://openalex.org/W1977556410","https://openalex.org/W1988604380","https://openalex.org/W1989265314","https://openalex.org/W1995459276","https://openalex.org/W1998654411","https://openalex.org/W2012076162","https://openalex.org/W2028501442","https://openalex.org/W2047817492","https://openalex.org/W2079195157","https://openalex.org/W2079246731","https://openalex.org/W2109628770","https://openalex.org/W2113586398","https://openalex.org/W2148714761","https://openalex.org/W2342408036","https://openalex.org/W2504718941","https://openalex.org/W2610323442","https://openalex.org/W2613274667","https://openalex.org/W2618782758","https://openalex.org/W2627014343","https://openalex.org/W2742989960","https://openalex.org/W2751490822","https://openalex.org/W2766611958","https://openalex.org/W2778613407","https://openalex.org/W2790747112","https://openalex.org/W2791079235","https://openalex.org/W2801522993","https://openalex.org/W2809840499","https://openalex.org/W2887126012","https://openalex.org/W2923933476","https://openalex.org/W2936650651","https://openalex.org/W2945277272","https://openalex.org/W2946376248","https://openalex.org/W2962874036","https://openalex.org/W2969003068","https://openalex.org/W2981207057","https://openalex.org/W2994808218","https://openalex.org/W2997073788","https://openalex.org/W3008790764","https://openalex.org/W3043110585","https://openalex.org/W3044811479","https://openalex.org/W3080329174","https://openalex.org/W3089786814","https://openalex.org/W3103044453","https://openalex.org/W3145694833","https://openalex.org/W3165137932","https://openalex.org/W3169906434","https://openalex.org/W3185318183","https://openalex.org/W3187933708","https://openalex.org/W3191097593","https://openalex.org/W3192047529","https://openalex.org/W4232120137","https://openalex.org/W4251129659","https://openalex.org/W4255815195","https://openalex.org/W4300995828","https://openalex.org/W6690887618"],"related_works":["https://openalex.org/W4385957992","https://openalex.org/W4229521721","https://openalex.org/W2061473111","https://openalex.org/W2215058820","https://openalex.org/W2559419175","https://openalex.org/W2245014125","https://openalex.org/W1994673457","https://openalex.org/W2405411278","https://openalex.org/W2112004925","https://openalex.org/W1560170243"],"abstract_inverted_index":{"Train":[0],"delay":[1,32,36,55,68,87,100,107,192,222,236],"evolutions":[2],"exhibit":[3],"different":[4,95],"patterns":[5],"(i.e.,":[6],"increasing":[7],"delays,":[8,10],"decreasing":[9],"or":[11],"unchanged":[12],"delays),":[13],"because":[14,228],"of":[15,18,29,53,105,137,211,229,234],"the":[16,30,86,92,99,103,120,127,134,147,156,162,165,169,183,190,200,209,212,217,220,235],"effects":[17],"stochastic":[19],"disturbances":[20],"and":[21,27,65,90,154,168,204,215],"pre-scheduled":[22],"supplement/recovery":[23],"times.":[24],"The":[25,79,115,140,178],"dynamics":[26],"uncertainty":[28],"train":[31,35,67,138,153],"evolution":[33,56,88,237],"make":[34],"prediction":[37,69,193,223],"a":[38,44,54,61,66,106,112],"challenging":[39],"task.":[40],"This":[41],"study":[42],"presents":[43],"hybrid":[45],"framework,":[46],"called":[47],"context-driven":[48],"Bayesian":[49,72],"network":[50,73],"(CDBN),":[51],"composed":[52],"pattern":[57],"discovery":[58],"model,":[59,70,117,164,171],"i.e.,":[60,71,102],"K-Means":[62],"clustering":[63,80,148,166,201],"approach,":[64],"(BN),":[74],"to":[75,84,111,125,152],"address":[76],"this":[77],"problem.":[78],"algorithm":[81],"is":[82,131,202],"used":[83,132,151],"uncover":[85],"patterns,":[89],"classify":[91],"data":[93,141],"into":[94],"categories,":[96],"based":[97],"on":[98,196],"jumps,":[101],"change":[104],"from":[108],"one":[109],"station":[110],"consequent":[113],"station.":[114],"BN":[116,157,163,185],"which":[118],"considers":[119],"delays":[121],"in":[122,142,225],"previous":[123],"stations":[124],"overcome":[126],"Markov":[128,197],"property":[129],"assumption,":[130],"as":[133],"predictive":[135,213],"model":[136,158],"delays.":[139],"each":[143],"category":[144],"(classified":[145],"by":[146,172],"model)":[149],"are":[150],"test":[155],"separately.":[159],"We":[160],"evaluated":[161],"algorithm,":[167],"CDBN":[170,218],"comparing":[173],"against":[174],"their":[175],"counterparts,":[176],"respectively.":[177],"results":[179],"show":[180],"that:":[181],"(1)":[182],"proposed":[184],"structure":[186],"has":[187],"advantages":[188],"over":[189],"common":[191],"models":[194,224],"built":[195],"property;":[198],"(2)":[199],"effective,":[203],"it":[205],"can":[206],"extensively":[207],"improve":[208],"accuracy":[210],"model;":[214],"(3)":[216],"outperforms":[219],"existing":[221],"wide":[226],"usability,":[227],"its":[230],"more":[231],"profound":[232],"understanding":[233],"patterns.":[238]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":16},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":6}],"updated_date":"2026-03-04T09:10:02.777135","created_date":"2025-10-10T00:00:00"}