{"id":"https://openalex.org/W2981570580","doi":"https://doi.org/10.1109/tits.2019.2947145","title":"Attention-Based Deep Ensemble Net for Large-Scale Online Taxi-Hailing Demand Prediction","display_name":"Attention-Based Deep Ensemble Net for Large-Scale Online Taxi-Hailing Demand Prediction","publication_year":2019,"publication_date":"2019-10-23","ids":{"openalex":"https://openalex.org/W2981570580","doi":"https://doi.org/10.1109/tits.2019.2947145","mag":"2981570580"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2019.2947145","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2947145","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/A5100355854","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0002-3295-2917"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100320722","display_name":"Zhiyuan Liu","orcid":"https://orcid.org/0000-0002-6331-0810"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiyuan Liu","raw_affiliation_strings":["Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-6331-0810","affiliations":[{"raw_affiliation_string":"Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059827408","display_name":"Cheng Lyu","orcid":"https://orcid.org/0000-0002-6356-6947"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Lyu","raw_affiliation_strings":["Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, School of Mathematics, and School of Transportation, Southeast University, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-6356-6947","affiliations":[{"raw_affiliation_string":"Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, School of Mathematics, and School of Transportation, Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010419481","display_name":"Jieping Ye","orcid":"https://orcid.org/0000-0001-8662-5818"},"institutions":[{"id":"https://openalex.org/I4401726870","display_name":"Didi Chuxing (China)","ror":"https://ror.org/02ksqcf75","country_code":null,"type":"company","lineage":["https://openalex.org/I4401726870"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jieping Ye","raw_affiliation_strings":["Didi Research Institute, Didi Chuxing, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Didi Research Institute, Didi Chuxing, Beijing, China","institution_ids":["https://openalex.org/I4401726870"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.0587,"has_fulltext":false,"cited_by_count":48,"citation_normalized_percentile":{"value":0.93520852,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"21","issue":"11","first_page":"4798","last_page":"4807"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9991999864578247,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9980999827384949,"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":0.7157106399536133},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6546392440795898},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.6106759309768677},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.6099070310592651},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5478082895278931},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5437813997268677},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5072435736656189},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.47560247778892517},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.470355749130249},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.4252830743789673},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.13616952300071716},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.0837373435497284}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7157106399536133},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6546392440795898},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.6106759309768677},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6099070310592651},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5478082895278931},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5437813997268677},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5072435736656189},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.47560247778892517},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.470355749130249},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.4252830743789673},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.13616952300071716},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0837373435497284},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2019.2947145","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2019.2947145","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":"Sustainable cities and communities","score":0.8299999833106995,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G8860659139","display_name":null,"funder_award_id":"51638004","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":86,"referenced_works":["https://openalex.org/W28412257","https://openalex.org/W149424455","https://openalex.org/W1484210532","https://openalex.org/W1514535095","https://openalex.org/W1522301498","https://openalex.org/W1534477342","https://openalex.org/W1686810756","https://openalex.org/W1988580225","https://openalex.org/W2002370809","https://openalex.org/W2004353783","https://openalex.org/W2019370496","https://openalex.org/W2021836772","https://openalex.org/W2036785686","https://openalex.org/W2052250659","https://openalex.org/W2072128103","https://openalex.org/W2106251367","https://openalex.org/W2113298739","https://openalex.org/W2124868070","https://openalex.org/W2133564696","https://openalex.org/W2137278143","https://openalex.org/W2150757437","https://openalex.org/W2163605009","https://openalex.org/W2165991108","https://openalex.org/W2179352600","https://openalex.org/W2244750928","https://openalex.org/W2304609584","https://openalex.org/W2397299141","https://openalex.org/W2399456070","https://openalex.org/W2460896869","https://openalex.org/W2481401919","https://openalex.org/W2487087946","https://openalex.org/W2528639018","https://openalex.org/W2530386080","https://openalex.org/W2560473673","https://openalex.org/W2561238782","https://openalex.org/W2564701384","https://openalex.org/W2593182953","https://openalex.org/W2596628535","https://openalex.org/W2618530766","https://openalex.org/W2695874637","https://openalex.org/W2743316574","https://openalex.org/W2766311542","https://openalex.org/W2768348081","https://openalex.org/W2788134583","https://openalex.org/W2791779647","https://openalex.org/W2803620531","https://openalex.org/W2809128166","https://openalex.org/W2894714913","https://openalex.org/W2904832339","https://openalex.org/W2910829642","https://openalex.org/W2912934387","https://openalex.org/W2912985636","https://openalex.org/W2919115771","https://openalex.org/W2950124505","https://openalex.org/W2956067742","https://openalex.org/W2962826786","https://openalex.org/W2962960549","https://openalex.org/W2963077256","https://openalex.org/W2963124587","https://openalex.org/W2963403868","https://openalex.org/W2963420343","https://openalex.org/W2963542991","https://openalex.org/W2975127965","https://openalex.org/W2998704965","https://openalex.org/W3098722327","https://openalex.org/W4212883601","https://openalex.org/W4231109964","https://openalex.org/W4385245566","https://openalex.org/W6628927728","https://openalex.org/W6629368666","https://openalex.org/W6630875275","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6659849045","https://openalex.org/W6679434410","https://openalex.org/W6680171035","https://openalex.org/W6680532216","https://openalex.org/W6712249138","https://openalex.org/W6712635486","https://openalex.org/W6718644182","https://openalex.org/W6728547873","https://openalex.org/W6730179637","https://openalex.org/W6739901393","https://openalex.org/W6745609711","https://openalex.org/W6746218141","https://openalex.org/W6748555476"],"related_works":["https://openalex.org/W2794896638","https://openalex.org/W2358868262","https://openalex.org/W2891633941","https://openalex.org/W3202800081","https://openalex.org/W3101614107","https://openalex.org/W1909207154","https://openalex.org/W4390971112","https://openalex.org/W3036530763","https://openalex.org/W1514365828","https://openalex.org/W3149839747"],"abstract_inverted_index":{"How":[0],"to":[1,28,42,52,95,116],"effectively":[2],"ensemble":[3,22,38,91,112,119],"different":[4],"base":[5],"models":[6],"is":[7,40,85,114],"a":[8,86],"challenging":[9],"but":[10],"extremely":[11],"valuable":[12],"task.":[13],"This":[14],"study":[15],"focuses":[16],"on":[17,101],"the":[18,44,54,63,67,74,117,124],"construction":[19],"of":[20,62,88,123],"an":[21,35],"framework":[23],"designed":[24,41],"for":[25,78],"spatio-temporal":[26,97],"data":[27],"predict":[29],"large-scale":[30,96],"online":[31,103],"taxi-hailing":[32,104],"demand,":[33],"where":[34],"attention-based":[36,111],"deep":[37],"net":[39,113],"enhance":[43],"prediction":[45,125],"accuracy.":[46,126],"We":[47],"present":[48],"three":[49],"attention":[50,68],"blocks":[51],"model":[53],"inter-channel":[55],"relationship,":[56],"inter-spatial":[57],"relationship":[58,61],"and":[59],"position":[60],"feature":[64,76,80],"maps.":[65],"Then,":[66],"maps":[69],"can":[70],"be":[71],"multiplied":[72],"by":[73],"input":[75],"map":[77],"adaptive":[79],"refinement.":[81],"The":[82],"proposed":[83,110],"method":[84,92],"kind":[87],"commonly":[89],"used":[90],"which":[93],"applies":[94],"prediction.":[98],"Experimental":[99],"results":[100],"city-wide":[102],"demand":[105],"predictions":[106],"demonstrate":[107],"that":[108],"our":[109],"superior":[115],"existing":[118],"strategy":[120],"in":[121],"terms":[122]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}