{"id":"https://openalex.org/W2939540463","doi":"https://doi.org/10.1109/tits.2019.2918923","title":"Ensemble Convolutional Neural Networks for Mode Inference in Smartphone Travel Survey","display_name":"Ensemble Convolutional Neural Networks for Mode Inference in Smartphone Travel Survey","publication_year":2019,"publication_date":"2019-06-07","ids":{"openalex":"https://openalex.org/W2939540463","doi":"https://doi.org/10.1109/tits.2019.2918923","mag":"2939540463"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2019.2918923","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2918923","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":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1904.08933","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5047064024","display_name":"Ali Yazdizadeh","orcid":"https://orcid.org/0000-0003-1902-6561"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ali Yazdizadeh","raw_affiliation_strings":["Planning and Environment, Concordia University, Montreal, Canada","Department of Geography, Planning, and Environment Concordia University Montreal QC Canada"],"raw_orcid":"https://orcid.org/0000-0003-1902-6561","affiliations":[{"raw_affiliation_string":"Planning and Environment, Concordia University, Montreal, Canada","institution_ids":["https://openalex.org/I60158472"]},{"raw_affiliation_string":"Department of Geography, Planning, and Environment Concordia University Montreal QC Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022678420","display_name":"Zachary Patterson","orcid":"https://orcid.org/0000-0001-8878-7845"},"institutions":[{"id":"https://openalex.org/I60158472","display_name":"Concordia University","ror":"https://ror.org/0420zvk78","country_code":"CA","type":"education","lineage":["https://openalex.org/I60158472"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Zachary Patterson","raw_affiliation_strings":["Planning and Environment, Concordia University, Montreal, Canada","Department of Geography, Planning, and Environment Concordia University Montreal QC Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Planning and Environment, Concordia University, Montreal, Canada","institution_ids":["https://openalex.org/I60158472"]},{"raw_affiliation_string":"Department of Geography, Planning, and Environment Concordia University Montreal QC Canada","institution_ids":["https://openalex.org/I60158472"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048496396","display_name":"Bilal Farooq","orcid":"https://orcid.org/0000-0003-1980-5645"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Bilal Farooq","raw_affiliation_strings":["Ryerson University, Toronto, Canada","[Department of Civil Engineering, Ryerson University, Toronto, ON, Canada.]"],"raw_orcid":"https://orcid.org/0000-0003-1980-5645","affiliations":[{"raw_affiliation_string":"Ryerson University, Toronto, Canada","institution_ids":["https://openalex.org/I530967"]},{"raw_affiliation_string":"[Department of Civil Engineering, Ryerson University, Toronto, ON, Canada.]","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7079,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.79767452,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"21","issue":"6","first_page":"2232","last_page":"2239"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9998999834060669,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9998999834060669,"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/T10298","display_name":"Urban Transport and Accessibility","score":0.9976999759674072,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9968000054359436,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.7672826051712036},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7198823690414429},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6533433198928833},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6353437304496765},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.6163541674613953},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6043421030044556},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5535792708396912},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.549019455909729},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.5414947867393494},{"id":"https://openalex.org/keywords/mode","display_name":"Mode (computer interface)","score":0.5099195241928101},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5056140422821045},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45021939277648926},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4167681336402893},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4151102304458618},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36998841166496277},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1109766960144043}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.7672826051712036},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7198823690414429},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6533433198928833},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6353437304496765},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.6163541674613953},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6043421030044556},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5535792708396912},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.549019455909729},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.5414947867393494},{"id":"https://openalex.org/C48677424","wikidata":"https://www.wikidata.org/wiki/Q6888088","display_name":"Mode (computer interface)","level":2,"score":0.5099195241928101},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5056140422821045},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45021939277648926},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4167681336402893},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4151102304458618},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36998841166496277},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1109766960144043},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"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/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tits.2019.2918923","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2918923","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"},{"id":"pmh:oai:arXiv.org:1904.08933","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1904.08933","pdf_url":"https://arxiv.org/pdf/1904.08933","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2939540463","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1904.08933","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1904.08933","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1904.08933","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1904.08933","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1904.08933","pdf_url":"https://arxiv.org/pdf/1904.08933","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4542538021","display_name":null,"funder_award_id":"890-2015-0022","funder_id":"https://openalex.org/F4320334617","funder_display_name":"Social Sciences and Humanities Research Council of Canada"},{"id":"https://openalex.org/G4812621456","display_name":null,"funder_award_id":"950-224364","funder_id":"https://openalex.org/F4320320994","funder_display_name":"Canada Research Chairs"}],"funders":[{"id":"https://openalex.org/F4320314000","display_name":"Compute Canada","ror":"https://ror.org/03ty8yr27"},{"id":"https://openalex.org/F4320314005","display_name":"Western Canada Research Grid","ror":null},{"id":"https://openalex.org/F4320320994","display_name":"Canada Research Chairs","ror":"https://ror.org/0517h6h17"},{"id":"https://openalex.org/F4320334617","display_name":"Social Sciences and Humanities Research Council of Canada","ror":"https://ror.org/04j5jqy92"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2939540463.pdf","grobid_xml":"https://content.openalex.org/works/W2939540463.grobid-xml"},"referenced_works_count":23,"referenced_works":["https://openalex.org/W1613249581","https://openalex.org/W1932847118","https://openalex.org/W2049395331","https://openalex.org/W2091372472","https://openalex.org/W2136317921","https://openalex.org/W2156876426","https://openalex.org/W2163605009","https://openalex.org/W2301959859","https://openalex.org/W2304648132","https://openalex.org/W2342216031","https://openalex.org/W2411089289","https://openalex.org/W2544649410","https://openalex.org/W2557283755","https://openalex.org/W2590038026","https://openalex.org/W2607306668","https://openalex.org/W2616570228","https://openalex.org/W2752546456","https://openalex.org/W2771098373","https://openalex.org/W2896730331","https://openalex.org/W2962949934","https://openalex.org/W6683161558","https://openalex.org/W6684191040","https://openalex.org/W6697974390"],"related_works":["https://openalex.org/W3032494905","https://openalex.org/W3116183417","https://openalex.org/W2997514867","https://openalex.org/W3160576548","https://openalex.org/W2358474461","https://openalex.org/W2913542416","https://openalex.org/W3205415752","https://openalex.org/W3119162813","https://openalex.org/W2104813983","https://openalex.org/W1538835152","https://openalex.org/W3102697733","https://openalex.org/W2583112160","https://openalex.org/W1511048421","https://openalex.org/W2912528874","https://openalex.org/W2954268824","https://openalex.org/W2569418206","https://openalex.org/W2791103717","https://openalex.org/W2382850429","https://openalex.org/W2036928248","https://openalex.org/W1613647457"],"abstract_inverted_index":{"We":[0],"develop":[1],"ensemble":[2,29,70,82,99],"convolutional":[3],"neural":[4],"networks":[5],"(CNNs)":[6],"to":[7,130],"classify":[8],"the":[9,52,69,96,108],"transportation":[10],"mode":[11],"of":[12,18,33,36,54,92,134],"trip":[13],"data":[14],"collected":[15],"as":[16,78,87],"part":[17],"a":[19,34,74,79],"large-scale":[20],"smartphone":[21],"travel":[22],"survey":[23],"in":[24,107,119],"Montreal,":[25],"Canada.":[26],"Our":[27],"proposed":[28],"library":[30,71],"is":[31,128],"composed":[32],"series":[35],"CNN":[37,44,55],"models":[38,56,105],"with":[39,84],"different":[40],"hyper-parameter":[41],"values":[42],"and":[43,62,102,113],"architectures.":[45],"In":[46],"our":[47],"final":[48],"model,":[49],"we":[50,67],"combine":[51],"output":[53],"using":[57],"\u201caverage":[58,126],"voting,\u201d":[59,61],"\u201cmajority":[60,111],"\u201coptimal":[63,114],"weights\u201d":[64,115],"methods.":[65],"Furthermore,":[66],"exploit":[68],"by":[72],"deploying":[73],"random":[75,85],"forest":[76,86],"model":[77],"meta-learner.":[80],"The":[81,110],"method":[83],"meta-learner":[88],"shows":[89],"an":[90,132],"accuracy":[91,121,133],"91.8%":[93],"which":[94],"surpasses":[95],"other":[97,103],"three":[98],"combination":[100,116],"methods,":[101],"comparable":[104],"reported":[106],"literature.":[109],"voting\u201d":[112,127],"methods":[117],"result":[118],"prediction":[120],"rates":[122],"around":[123],"89%,":[124],"while":[125],"able":[129],"achieve":[131],"only":[135],"85%.":[136]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2025-10-10T00:00:00"}
