{"id":"https://openalex.org/W2799612587","doi":"https://doi.org/10.1061/(asce)cp.1943-5487.0000752","title":"Spatial Transferability of Neural Network Models in Travel Demand Modeling","display_name":"Spatial Transferability of Neural Network Models in Travel Demand Modeling","publication_year":2018,"publication_date":"2018-04-17","ids":{"openalex":"https://openalex.org/W2799612587","doi":"https://doi.org/10.1061/(asce)cp.1943-5487.0000752","mag":"2799612587"},"language":"en","primary_location":{"id":"doi:10.1061/(asce)cp.1943-5487.0000752","is_oa":false,"landing_page_url":"https://doi.org/10.1061/(asce)cp.1943-5487.0000752","pdf_url":null,"source":{"id":"https://openalex.org/S176637136","display_name":"Journal of Computing in Civil Engineering","issn_l":"0887-3801","issn":["0887-3801","1943-5487"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315747","host_organization_name":"American Society of Civil Engineers","host_organization_lineage":["https://openalex.org/P4310315747"],"host_organization_lineage_names":["American Society of Civil Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing in Civil Engineering","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/A5101764605","display_name":"Liang Tang","orcid":"https://orcid.org/0000-0003-4138-1543"},"institutions":[{"id":"https://openalex.org/I116545467","display_name":"University of Mary","ror":"https://ror.org/055f0jp24","country_code":"US","type":"education","lineage":["https://openalex.org/I116545467"]},{"id":"https://openalex.org/I4210142152","display_name":"ORCID","ror":"https://ror.org/04fa4r544","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210142152"]},{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Liang Tang","raw_affiliation_strings":["Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Univ. of Maryland, 1173 Glenn Martin Hall, College Park, MD 20742. ORCID: ","Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Univ. of Maryland, 1173 Glenn Martin Hall, College Park, MD 20742. ORCID: https://orcid.org/0000-0003-4138-1543. E-mail:"],"raw_orcid":"https://orcid.org/0000-0003-4138-1543","affiliations":[{"raw_affiliation_string":"Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Univ. of Maryland, 1173 Glenn Martin Hall, College Park, MD 20742. ORCID: ","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"Graduate Research Assistant, Dept. of Civil and Environmental Engineering, Univ. of Maryland, 1173 Glenn Martin Hall, College Park, MD 20742. ORCID: https://orcid.org/0000-0003-4138-1543. E-mail:","institution_ids":["https://openalex.org/I4210142152","https://openalex.org/I116545467","https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037774759","display_name":"Chenfeng Xiong","orcid":"https://orcid.org/0000-0003-4237-1750"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenfeng Xiong","raw_affiliation_strings":["Assistant Research Professor, Dept. of Civil and Environmental Engineering, Univ. of Maryland, 1173 Glenn Martin Hall, College Park, MD 20742","Assistant Research Professor, Dept. of Civil and Environmental Engineering, Univ. of Maryland, 1173 Glenn Martin Hall, College Park, MD 20742. E-mail:"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Assistant Research Professor, Dept. of Civil and Environmental Engineering, Univ. of Maryland, 1173 Glenn Martin Hall, College Park, MD 20742","institution_ids":["https://openalex.org/I66946132"]},{"raw_affiliation_string":"Assistant Research Professor, Dept. of Civil and Environmental Engineering, Univ. of Maryland, 1173 Glenn Martin Hall, College Park, MD 20742. E-mail:","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100433907","display_name":"Lei Zhang","orcid":"https://orcid.org/0000-0002-3372-6321"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Lei Zhang","raw_affiliation_strings":["Herbert Rabin Distinguished Professor, Dept. of Civil and Environmental Engineering, Univ. of Maryland, 1173 Glenn Martin Hall, College Park, MD 20742 (corresponding author)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Herbert Rabin Distinguished Professor, Dept. of Civil and Environmental Engineering, Univ. of Maryland, 1173 Glenn Martin Hall, College Park, MD 20742 (corresponding author)","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100433907"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":1.7045,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.86919538,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"32","issue":"3","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"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"}},"topics":[{"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9975000023841858,"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/T10298","display_name":"Urban Transport and Accessibility","score":0.9950000047683716,"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/transferability","display_name":"Transferability","score":0.7723016738891602},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6420928239822388},{"id":"https://openalex.org/keywords/metropolitan-area","display_name":"Metropolitan area","score":0.6129655241966248},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.60765540599823},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6046854853630066},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5848633646965027},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.569796085357666},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.4549630582332611},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36903947591781616},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3464953303337097},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33557644486427307},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.22449958324432373}],"concepts":[{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.7723016738891602},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6420928239822388},{"id":"https://openalex.org/C158739034","wikidata":"https://www.wikidata.org/wiki/Q1907114","display_name":"Metropolitan area","level":2,"score":0.6129655241966248},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.60765540599823},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6046854853630066},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5848633646965027},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.569796085357666},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.4549630582332611},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36903947591781616},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3464953303337097},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33557644486427307},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.22449958324432373},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C140331021","wikidata":"https://www.wikidata.org/wiki/Q1868104","display_name":"Logit","level":2,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1061/(asce)cp.1943-5487.0000752","is_oa":false,"landing_page_url":"https://doi.org/10.1061/(asce)cp.1943-5487.0000752","pdf_url":null,"source":{"id":"https://openalex.org/S176637136","display_name":"Journal of Computing in Civil Engineering","issn_l":"0887-3801","issn":["0887-3801","1943-5487"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315747","host_organization_name":"American Society of Civil Engineers","host_organization_lineage":["https://openalex.org/P4310315747"],"host_organization_lineage_names":["American Society of Civil Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing in Civil Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.6200000047683716}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332393","display_name":"Federal Highway Administration","ror":"https://ror.org/0473rr271"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W167016754","https://openalex.org/W616684754","https://openalex.org/W1533970595","https://openalex.org/W1587621164","https://openalex.org/W1607624180","https://openalex.org/W1888747018","https://openalex.org/W1967444754","https://openalex.org/W1985765969","https://openalex.org/W1988942353","https://openalex.org/W1991951994","https://openalex.org/W1992852093","https://openalex.org/W1999943939","https://openalex.org/W2001550469","https://openalex.org/W2003998940","https://openalex.org/W2008900804","https://openalex.org/W2029223998","https://openalex.org/W2031088755","https://openalex.org/W2048429520","https://openalex.org/W2050101777","https://openalex.org/W2051904810","https://openalex.org/W2070348058","https://openalex.org/W2081762866","https://openalex.org/W2082329414","https://openalex.org/W2093947671","https://openalex.org/W2111373303","https://openalex.org/W2114326128","https://openalex.org/W2114367267","https://openalex.org/W2153946462","https://openalex.org/W2154087025","https://openalex.org/W2159167759","https://openalex.org/W2160607820","https://openalex.org/W2161221533","https://openalex.org/W2164922106","https://openalex.org/W2166982344","https://openalex.org/W2616198738","https://openalex.org/W2738159428","https://openalex.org/W4244207479"],"related_works":["https://openalex.org/W4308262314","https://openalex.org/W4382286161","https://openalex.org/W2960456850","https://openalex.org/W3021430260","https://openalex.org/W4281645081","https://openalex.org/W2946016983","https://openalex.org/W4312200629","https://openalex.org/W4317565044","https://openalex.org/W3015887428","https://openalex.org/W2883641150"],"abstract_inverted_index":{"Neural":[0],"network":[1],"(NN)":[2],"models":[3,35,99,119,147,165],"have":[4,191],"been":[5],"widely":[6],"used":[7],"in":[8,12,36,41,61,107],"travel":[9,37],"demand":[10,38],"modeling":[11],"recently":[13],"years.":[14],"However,":[15],"there":[16],"are":[17,59,83,100],"few":[18],"studies":[19],"about":[20],"the":[21,30,51,74,86,108,116,123,142,161,172,194],"spatial":[22,31,129],"transferability":[23,32,130,162],"of":[24,33,53,115,145,163,171,182],"NN":[25,34,67,98,118,146,164,196],"models.":[26],"In":[27],"this":[28],"paper,":[29],"modeling,":[39],"especially":[40],"mode":[42],"choice":[43],"models,":[44],"is":[45,71,120,166,176],"analyzed.":[46],"This":[47],"paper":[48],"first":[49],"discusses":[50],"performance":[52,136,170,202],"na\u00efve":[54,143,212],"transfer":[55,144,187],"when":[56,79],"no":[57],"data":[58,82],"available":[60],"an":[62],"application":[63],"context.":[64],"Then,":[65],"a":[66,206],"model":[68,197],"adaptation":[69,174,198],"method":[70,175,199],"proposed":[72,173,195],"using":[73,102,131],"classification":[75],"adjustment":[76],"weight":[77],"vector":[78],"limited":[80],"local":[81,183],"available.":[84],"Using":[85],"2007/2008":[87],"Transportation":[88],"Planning":[89],"Board\u2014Baltimore":[90],"Metropolitan":[91],"Council":[92],"Household":[93],"Travel":[94],"Survey":[95],"data,":[96],"five":[97,105,117],"built":[101],"trips":[103],"within":[104],"areas":[106,126,153,189],"Washington,":[109],"DC,":[110],"and":[111,134],"Baltimore":[112],"regions.":[113],"Each":[114],"applied":[121],"to":[122,127,211],"other":[124],"four":[125],"study":[128],"both":[132],"individual-level":[133],"aggregate-level":[135],"measures.":[137],"The":[138,169],"result":[139],"shows":[140],"that":[141,154,190],"can":[148,200],"perform":[149],"very":[150],"well":[151],"between":[152,188],"share":[155],"many":[156],"similarities.":[157],"It":[158],"also":[159],"indicates":[160],"not":[167],"symmetric.":[168],"evaluated":[177],"for":[178],"different":[179],"sample":[180,208],"sizes":[181],"training":[184],"data.":[185],"For":[186],"significant":[192],"differences,":[193],"improve":[201],"significantly,":[203],"even":[204],"with":[205],"small":[207],"size,":[209],"compared":[210],"transfer.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
