{"id":"https://openalex.org/W4393384665","doi":"https://doi.org/10.1007/s40747-024-01391-6","title":"Short-term origin\u2013destination flow prediction for urban rail network: a deep learning method based on multi-source big data","display_name":"Short-term origin\u2013destination flow prediction for urban rail network: a deep learning method based on multi-source big data","publication_year":2024,"publication_date":"2024-04-01","ids":{"openalex":"https://openalex.org/W4393384665","doi":"https://doi.org/10.1007/s40747-024-01391-6"},"language":"en","primary_location":{"id":"doi:10.1007/s40747-024-01391-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-024-01391-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-024-01391-6.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex &amp; Intelligent Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s40747-024-01391-6.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067439053","display_name":"Hongmeng Cui","orcid":"https://orcid.org/0009-0002-4277-9799"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hongmeng Cui","raw_affiliation_strings":["School of Systems Science, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Systems Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036032006","display_name":"Bingfeng Si","orcid":"https://orcid.org/0000-0001-9304-9679"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingfeng Si","raw_affiliation_strings":["School of Systems Science, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Systems Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103979720","display_name":"Jiayuan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiayuan Wang","raw_affiliation_strings":["School of Systems Science, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Systems Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108248360","display_name":"Ben Y. Zhao","orcid":"https://orcid.org/0009-0003-8909-0494"},"institutions":[{"id":"https://openalex.org/I4210167045","display_name":"Shanxi Transportation Research Institute","ror":"https://ror.org/05y7veh17","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210167045"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ben Zhao","raw_affiliation_strings":["Shanxi Intelligent Transportation Institute Co., Ltd, Taiyuan, Shanxi, China"],"affiliations":[{"raw_affiliation_string":"Shanxi Intelligent Transportation Institute Co., Ltd, Taiyuan, Shanxi, China","institution_ids":["https://openalex.org/I4210167045"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065560622","display_name":"Weiting Pan","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiting Pan","raw_affiliation_strings":["School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Traffic and Transportation, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5067439053"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":{"value":1320,"currency":"GBP","value_usd":1619},"apc_paid":{"value":1320,"currency":"GBP","value_usd":1619},"fwci":1.2895,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.77164787,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"10","issue":"4","first_page":"4675","last_page":"4696"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"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":1.0,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9991999864578247,"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":0.9894000291824341,"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/computer-science","display_name":"Computer science","score":0.7240215539932251},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.557189404964447},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.5154514908790588},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49830102920532227},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4865759611129761},{"id":"https://openalex.org/keywords/beijing","display_name":"Beijing","score":0.4653851091861725},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.45544883608818054},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.421225368976593},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35543179512023926}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7240215539932251},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.557189404964447},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.5154514908790588},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49830102920532227},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4865759611129761},{"id":"https://openalex.org/C2778304055","wikidata":"https://www.wikidata.org/wiki/Q657474","display_name":"Beijing","level":3,"score":0.4653851091861725},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.45544883608818054},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.421225368976593},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35543179512023926},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"id":"https://openalex.org/C191935318","wikidata":"https://www.wikidata.org/wiki/Q148","display_name":"China","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s40747-024-01391-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-024-01391-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-024-01391-6.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex &amp; Intelligent Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:0cc4933ad6bc4e72a0c742cba97224d4","is_oa":true,"landing_page_url":"https://doaj.org/article/0cc4933ad6bc4e72a0c742cba97224d4","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":"Complex & Intelligent Systems, Vol 10, Iss 4, Pp 4675-4696 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s40747-024-01391-6","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s40747-024-01391-6","pdf_url":"https://link.springer.com/content/pdf/10.1007/s40747-024-01391-6.pdf","source":{"id":"https://openalex.org/S3035462843","display_name":"Complex & Intelligent Systems","issn_l":"2198-6053","issn":["2198-6053","2199-4536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Complex &amp; Intelligent Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8299999833106995,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G2087396116","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2364846781","display_name":null,"funder_award_id":"72091513","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G2376276132","display_name":null,"funder_award_id":"China","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4020255992","display_name":null,"funder_award_id":"Project","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4308714863","display_name":null,"funder_award_id":"72091513<","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4997289634","display_name":null,"funder_award_id":"2022YJS067","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G5994120800","display_name":null,"funder_award_id":"Natural","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6809183074","display_name":null,"funder_award_id":"Project No.","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7601323162","display_name":null,"funder_award_id":"72288101","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G839615606","display_name":null,"funder_award_id":"72091513","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4393384665.pdf"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W1984017078","https://openalex.org/W1988580225","https://openalex.org/W1990816055","https://openalex.org/W2004353783","https://openalex.org/W2017439370","https://openalex.org/W2021406119","https://openalex.org/W2025382546","https://openalex.org/W2036785686","https://openalex.org/W2058560977","https://openalex.org/W2064675550","https://openalex.org/W2463449951","https://openalex.org/W2528639018","https://openalex.org/W2573587735","https://openalex.org/W2579495707","https://openalex.org/W2602173181","https://openalex.org/W2606105273","https://openalex.org/W2614121823","https://openalex.org/W2695874637","https://openalex.org/W2751650042","https://openalex.org/W2756203131","https://openalex.org/W2775717462","https://openalex.org/W2782738497","https://openalex.org/W2788134583","https://openalex.org/W2809923164","https://openalex.org/W2884738862","https://openalex.org/W2904753829","https://openalex.org/W2946160394","https://openalex.org/W2947812485","https://openalex.org/W2949685089","https://openalex.org/W2949732208","https://openalex.org/W2956452632","https://openalex.org/W2962790412","https://openalex.org/W2964121744","https://openalex.org/W2973065886","https://openalex.org/W2978273467","https://openalex.org/W2998652672","https://openalex.org/W2999696017","https://openalex.org/W3021182685","https://openalex.org/W3028195881","https://openalex.org/W3031609778","https://openalex.org/W3033535063","https://openalex.org/W3084394145","https://openalex.org/W3103720336","https://openalex.org/W3109254449","https://openalex.org/W3119688269","https://openalex.org/W3135788747","https://openalex.org/W3139241501","https://openalex.org/W3183749634","https://openalex.org/W3185889262","https://openalex.org/W3201364331","https://openalex.org/W4311374643","https://openalex.org/W4322716488","https://openalex.org/W4324027634"],"related_works":["https://openalex.org/W2905433371","https://openalex.org/W2888392564","https://openalex.org/W4310278675","https://openalex.org/W4388422664","https://openalex.org/W4390569940","https://openalex.org/W4361193272","https://openalex.org/W2963326959","https://openalex.org/W4388685194","https://openalex.org/W4312407344","https://openalex.org/W2894289927"],"abstract_inverted_index":{"Abstract":[0],"Short-term":[1],"prediction":[2,34,55,64],"of":[3,21,35,71,193],"origin\u2013destination":[4],"(OD)":[5],"flow":[6,38,166,185],"is":[7,18,58,96,110,127,151,201],"a":[8,62,88,105,122,171],"primary":[9],"but":[10],"complex":[11],"assignment":[12],"to":[13,60,112,129,154,181],"urban":[14,25],"rail":[15,26],"companies,":[16],"which":[17,138,160],"the":[19,68,72,131,156,162,191,194,217,226,231],"basis":[20],"intelligent":[22],"and":[23,30,47,84,134,167,214,216,229],"real-time":[24,168,179],"transit":[27],"(URT)":[28],"operation":[29],"management.":[31],"The":[32,98,198],"short-term":[33,54,92],"URT":[36,73],"OD":[37,74,119,165,184],"has":[39],"three":[40],"special":[41,69],"characteristics:":[42],"data":[43,45,48,132,135,157],"lag,":[44],"dimensionality,":[46],"malconformation,":[49],"distinguishing":[50],"it":[51,222],"from":[52,212],"other":[53],"tasks.":[56],"It":[57],"essential":[59],"propose":[61],"novel":[63],"algorithm":[65],"that":[66,221],"considers":[67],"characteristics":[70],"flow.":[75],"For":[76],"this":[77],"purpose,":[78],"based":[79],"on":[80,206],"deep":[81],"learning":[82,125],"methods":[83],"multi-source":[85],"big":[86],"data,":[87],"modified":[89],"spatial\u2013temporal":[90,176,227],"long":[91],"memory":[93],"(ST-LSTM)":[94],"model":[95,100,195,200],"established.":[97],"proposed":[99,153],"comprises":[101],"four":[102],"components:":[103],"(1)":[104],"temporal":[106],"feature":[107],"extraction":[108],"module":[109,126,173],"devised":[111],"extract":[113],"time":[114],"information":[115,180],"within":[116],"network-wide":[117],"historical":[118,175],"data;":[120],"(2)":[121],"spatial":[123,142],"correlation":[124,143],"introduced":[128],"address":[130],"malconformation":[133],"dimensionality":[136],"problems,":[137],"provides":[139],"an":[140,147],"interpretable":[141],"quantization":[144],"method;":[145],"(3)":[146],"input":[148],"control-gated":[149],"mechanism":[150],"originally":[152],"solve":[155],"lag":[158],"problem,":[159],"combines":[161,174],"processed":[163],"available":[164],"inflow/outflow;":[169],"(4)":[170],"fusion":[172],"features":[177],"with":[178],"achieve":[182],"accurate":[183],"prediction.":[186],"We":[187],"also":[188],"further":[189],"discuss":[190],"interpretability":[192],"in":[196],"detail.":[197],"ST-LSTM":[199],"evaluated":[202],"by":[203],"sufficient":[204],"experiments":[205],"two":[207],"large-scale":[208],"actual":[209],"subway":[210],"datasets":[211],"Nanjing":[213],"Beijing,":[215],"experimental":[218],"results":[219],"demonstrate":[220],"can":[223],"better":[224],"learn":[225],"correlations":[228],"exceed":[230],"rest":[232],"benchmarking":[233],"methods.":[234]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-15T08:11:43.952461","created_date":"2025-10-10T00:00:00"}
