{"id":"https://openalex.org/W2910913012","doi":"https://doi.org/10.1109/ieem.2018.8607368","title":"Clustering Subway Station Arrival Patterns Using Weighted Dynamic Time Warping","display_name":"Clustering Subway Station Arrival Patterns Using Weighted Dynamic Time Warping","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2910913012","doi":"https://doi.org/10.1109/ieem.2018.8607368","mag":"2910913012"},"language":"en","primary_location":{"id":"doi:10.1109/ieem.2018.8607368","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem.2018.8607368","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","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/A5100619422","display_name":"Rui Wang","orcid":"https://orcid.org/0000-0001-5958-2234"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Rui Wang","raw_affiliation_strings":["Department of Industrial and Systems Engineering, National University of Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100442866","display_name":"Nan Chen","orcid":"https://orcid.org/0000-0003-2495-5234"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Nan Chen","raw_affiliation_strings":["Department of Industrial and Systems Engineering, National University of Singapore, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100374122","display_name":"Chen Zhang","orcid":"https://orcid.org/0000-0002-4767-9597"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Zhang","raw_affiliation_strings":["Department of Industrial Engineering, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.179941,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"531","last_page":"535"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9988999962806702,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9988999962806702,"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/dynamic-time-warping","display_name":"Dynamic time warping","score":0.8439963459968567},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7746261358261108},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7224925756454468},{"id":"https://openalex.org/keywords/schedule","display_name":"Schedule","score":0.5928542017936707},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5555409789085388},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.48283228278160095},{"id":"https://openalex.org/keywords/timestamp","display_name":"Timestamp","score":0.4777340590953827},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4577241837978363},{"id":"https://openalex.org/keywords/arrival-time","display_name":"Arrival time","score":0.45564258098602295},{"id":"https://openalex.org/keywords/plan","display_name":"Plan (archaeology)","score":0.4113260805606842},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.2576908469200134},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23902186751365662},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13822531700134277},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11382395029067993}],"concepts":[{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.8439963459968567},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7746261358261108},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7224925756454468},{"id":"https://openalex.org/C68387754","wikidata":"https://www.wikidata.org/wiki/Q7271585","display_name":"Schedule","level":2,"score":0.5928542017936707},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5555409789085388},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.48283228278160095},{"id":"https://openalex.org/C113954288","wikidata":"https://www.wikidata.org/wiki/Q186885","display_name":"Timestamp","level":2,"score":0.4777340590953827},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4577241837978363},{"id":"https://openalex.org/C3017552255","wikidata":"https://www.wikidata.org/wiki/Q4135208","display_name":"Arrival time","level":2,"score":0.45564258098602295},{"id":"https://openalex.org/C2776505523","wikidata":"https://www.wikidata.org/wiki/Q4785468","display_name":"Plan (archaeology)","level":2,"score":0.4113260805606842},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.2576908469200134},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23902186751365662},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13822531700134277},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11382395029067993},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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":1,"locations":[{"id":"doi:10.1109/ieem.2018.8607368","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ieem.2018.8607368","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4399999976158142,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1606702997","https://openalex.org/W1698470199","https://openalex.org/W1971853044","https://openalex.org/W2002841906","https://openalex.org/W2007043321","https://openalex.org/W2008348094","https://openalex.org/W2008467464","https://openalex.org/W2037027640","https://openalex.org/W2044985623","https://openalex.org/W2047235845","https://openalex.org/W2085987121","https://openalex.org/W2091921805","https://openalex.org/W2128160875","https://openalex.org/W2137469723","https://openalex.org/W2151748186","https://openalex.org/W2243059988","https://openalex.org/W4252783439","https://openalex.org/W6690661240"],"related_works":["https://openalex.org/W2060561905","https://openalex.org/W1417711376","https://openalex.org/W2341338763","https://openalex.org/W2950183183","https://openalex.org/W2030799363","https://openalex.org/W2032415964","https://openalex.org/W2288425735","https://openalex.org/W2349923317","https://openalex.org/W2894081631","https://openalex.org/W2084517699"],"abstract_inverted_index":{"To":[0],"better":[1,101],"plan":[2],"and":[3,61,107],"schedule":[4],"public":[5],"transportation":[6],"resources,":[7],"it":[8],"is":[9,100],"crucial":[10],"to":[11,78],"understand":[12],"the":[13,29,37,52,58,93],"travel":[14,59],"demand":[15,30],"from":[16,83],"any":[17,20],"location":[18],"at":[19,41],"time.":[21],"In":[22],"this":[23],"article,":[24],"we":[25],"focus":[26],"on":[27,36],"analyzing":[28],"patterns":[31,82],"for":[32],"subway":[33],"stations":[34],"based":[35],"tap":[38],"in":[39,64,91],"data":[40,113],"each":[42],"station":[43],"entrance.":[44],"It":[45],"has":[46],"been":[47],"reported":[48],"that":[49],"accurately":[50],"predicting":[51],"arrival":[53],"rates":[54],"can":[55,88],"help":[56],"improve":[57],"experience,":[60],"prevent":[62],"over-crowding":[63],"train":[65],"carriages":[66],"or":[67],"platforms.":[68],"We":[69,103],"proposed":[70],"a":[71,111],"weighted":[72],"dynamic":[73],"time":[74],"warping":[75],"approach":[76,106],"(WDTW)":[77],"adaptively":[79],"cluster":[80],"similar":[81],"multiple":[84],"stations.":[85],"These":[86],"similarities":[87],"be":[89],"exploited":[90],"improving":[92],"prediction":[94],"performance":[95],"because":[96],"spatial":[97],"temporal":[98],"information":[99],"utilized.":[102],"demonstrated":[104],"our":[105],"its":[108],"effectiveness":[109],"through":[110],"real":[112],"example.":[114]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}