{"id":"https://openalex.org/W3043110585","doi":"https://doi.org/10.1109/tits.2020.3002785","title":"Intelligent Prediction of Train Delay Changes and Propagation Using RVFLNs With Improved Transfer Learning and Ensemble Learning","display_name":"Intelligent Prediction of Train Delay Changes and Propagation Using RVFLNs With Improved Transfer Learning and Ensemble Learning","publication_year":2020,"publication_date":"2020-07-14","ids":{"openalex":"https://openalex.org/W3043110585","doi":"https://doi.org/10.1109/tits.2020.3002785","mag":"3043110585"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2020.3002785","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2020.3002785","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/A5047383541","display_name":"Ping Zhou","orcid":"https://orcid.org/0000-0002-9398-172X"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ping Zhou","raw_affiliation_strings":["State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China.(e-mail: zhouping@mail.neu.edu.cn)"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China.(e-mail: zhouping@mail.neu.edu.cn)","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058343173","display_name":"Lefang Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lefang Chen","raw_affiliation_strings":["State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101810760","display_name":"Xuewu Dai","orcid":"https://orcid.org/0000-0002-9324-5925"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuewu Dai","raw_affiliation_strings":["State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075232357","display_name":"Baoxu Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baoxu Li","raw_affiliation_strings":["Institute of Quality and Technology Supervision, China Railway Shenyang Group Company Ltd., Shenyang, China","[Institute of Quality and Technology Supervision, China Railway Shenyang Group Company Ltd., Shenyang 110001, China.]"],"affiliations":[{"raw_affiliation_string":"Institute of Quality and Technology Supervision, China Railway Shenyang Group Company Ltd., Shenyang, China","institution_ids":[]},{"raw_affiliation_string":"[Institute of Quality and Technology Supervision, China Railway Shenyang Group Company Ltd., Shenyang 110001, China.]","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042520521","display_name":"Tianyou Chai","orcid":"https://orcid.org/0000-0002-4623-1483"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianyou Chai","raw_affiliation_strings":["State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China"],"affiliations":[{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5047383541"],"corresponding_institution_ids":["https://openalex.org/I9224756"],"apc_list":null,"apc_paid":null,"fwci":4.1484,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.9438837,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"22","issue":"12","first_page":"7432","last_page":"7444"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11568","display_name":"Railway Systems and Energy Efficiency","score":0.9975000023841858,"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":0.9975000023841858,"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/T10842","display_name":"Railway Engineering and Dynamics","score":0.9970999956130981,"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"}},{"id":"https://openalex.org/T12371","display_name":"Electrical Contact Performance and Analysis","score":0.9943000078201294,"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/computer-science","display_name":"Computer science","score":0.7220103144645691},{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.665267825126648},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6150490045547485},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6063063144683838},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5619156956672668},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5396426320075989},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.537405788898468},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4252523183822632},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3327583074569702}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7220103144645691},{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.665267825126648},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6150490045547485},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6063063144683838},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5619156956672668},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5396426320075989},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.537405788898468},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4252523183822632},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3327583074569702},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2020.3002785","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2020.3002785","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":[{"display_name":"Industry, innovation and infrastructure","score":0.6399999856948853,"id":"https://metadata.un.org/sdg/9"}],"awards":[{"id":"https://openalex.org/G1829930775","display_name":null,"funder_award_id":"61890934","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2665898191","display_name":null,"funder_award_id":"61790574","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6532033821","display_name":null,"funder_award_id":"U1834211","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7403195186","display_name":null,"funder_award_id":"N180802003","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G8587035357","display_name":null,"funder_award_id":"61790572","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8926609703","display_name":null,"funder_award_id":"XLYC1907132","funder_id":"https://openalex.org/F4320329895","funder_display_name":"Liaoning Revitalization Talents Program"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329895","display_name":"Liaoning Revitalization Talents Program","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1588282782","https://openalex.org/W1965236874","https://openalex.org/W1987859285","https://openalex.org/W1988604380","https://openalex.org/W2002520482","https://openalex.org/W2012638612","https://openalex.org/W2018855219","https://openalex.org/W2042184006","https://openalex.org/W2059477850","https://openalex.org/W2096943734","https://openalex.org/W2115403315","https://openalex.org/W2144382499","https://openalex.org/W2148143831","https://openalex.org/W2161548576","https://openalex.org/W2165698076","https://openalex.org/W2177253070","https://openalex.org/W2355560926","https://openalex.org/W2363187196","https://openalex.org/W2384074430","https://openalex.org/W2567617232","https://openalex.org/W2610323442","https://openalex.org/W2618782758","https://openalex.org/W2742989960","https://openalex.org/W2791079235","https://openalex.org/W2887126012","https://openalex.org/W2914898463","https://openalex.org/W2924937155","https://openalex.org/W2945277272","https://openalex.org/W2953013376","https://openalex.org/W2963693396","https://openalex.org/W2969003068","https://openalex.org/W2997073788","https://openalex.org/W3008790764","https://openalex.org/W6764152765","https://openalex.org/W7011303468","https://openalex.org/W7024943538"],"related_works":["https://openalex.org/W618248309","https://openalex.org/W2377336366","https://openalex.org/W1568097102","https://openalex.org/W4390419160","https://openalex.org/W1601203902","https://openalex.org/W2075798043","https://openalex.org/W2102464536","https://openalex.org/W4385398839","https://openalex.org/W4384700341","https://openalex.org/W4394759804"],"abstract_inverted_index":{"In":[0,46],"railway":[1,42,213],"operation,":[2],"train":[3,30,63,118,187,208],"delays":[4,64,154,188],"may":[5,20],"occur":[6],"due":[7],"to":[8,25,37,44,79,109,129,137,168],"various":[9],"reasons":[10],"(e.g.":[11],"severe":[12],"weather,":[13],"infrastructure":[14],"failure,":[15],"human":[16],"factors,":[17],"etc.)":[18],"and":[19,22,33,60,75,116,178,184,194],"change":[21],"spread":[23],"rapidly":[24],"subsequent":[26,171],"trains.":[27],"Prediction":[28],"of":[29,62,84,104,114,143,186,196],"delay":[31,106,134],"changes":[32,59],"propagation":[34,61,182],"is":[35,53,99,127],"important":[36],"provide":[38],"decision-making":[39],"support":[40],"for":[41,55,101,148],"dispatchers":[43],"reschedule.":[45],"this":[47],"paper,":[48],"a":[49,89],"multi-stage":[50],"intelligent":[51],"method":[52,199],"proposed":[54,100,128,162,198],"predicting":[56],"the":[57,81,85,105,111,132,141,144,158,161,170,176,181,197],"dynamic":[58],"using":[65,203],"random":[66],"vector":[67],"functional-link":[68],"networks":[69],"(RVFLNs)":[70],"with":[71,140],"improved":[72,91,121,145],"transfer":[73,122],"learning":[74,94,123],"ensemble":[76,93],"learning.":[77],"First,":[78],"improve":[80],"prediction":[82,102,179],"performance":[83],"single":[86],"RVFLNs":[87,95,124],"model,":[88],"novel":[90],"Stacking":[92],"(SRN)":[96],"regression":[97],"algorithm":[98,147,164],"modeling":[103],"changes.":[107],"Then,":[108],"ensure":[110],"classification":[112,177],"accuracy":[113],"unlabeled":[115],"class-imbalanced":[117],"data,":[119],"an":[120],"(ITRN)":[125],"classifier":[126],"decide":[130],"whether":[131],"initial":[133],"will":[135,165],"lead":[136],"associated":[138,153,172],"delays,":[139],"aid":[142],"SMOTE":[146],"processing":[149],"imbalanced":[150],"data.":[151],"If":[152],"are":[155,200],"identified":[156],"by":[157,202],"ITRN":[159],"classifier,":[160],"SRN":[163],"be":[166,190],"further":[167],"predict":[169],"delays.":[173],"By":[174],"iterating":[175],"procedures,":[180],"range":[183],"chain":[185],"can":[189],"obtained.":[191],"The":[192],"effectiveness":[193],"practicability":[195],"verified":[201],"two":[204],"experiments":[205],"against":[206],"actual":[207],"graph":[209],"data":[210],"from":[211],"different":[212],"lines.":[214]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":12},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":4}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}