{"id":"https://openalex.org/W4408689902","doi":"https://doi.org/10.1145/3716895.3716996","title":"Urban Transportation Passenger Flow Prediction Based on Multi-Model Decision Fusion","display_name":"Urban Transportation Passenger Flow Prediction Based on Multi-Model Decision Fusion","publication_year":2024,"publication_date":"2024-11-08","ids":{"openalex":"https://openalex.org/W4408689902","doi":"https://doi.org/10.1145/3716895.3716996"},"language":"en","primary_location":{"id":"doi:10.1145/3716895.3716996","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3716895.3716996","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Artificial Intelligence and Computer Engineering","raw_type":"proceedings-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":null,"display_name":"Yuxin Yang","orcid":"https://orcid.org/0009-0000-2610-0331"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxin Yang","raw_affiliation_strings":["School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, Sichuan, China"],"raw_orcid":"https://orcid.org/0009-0000-2610-0331","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, Sichuan, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qianxue Bai","orcid":"https://orcid.org/0009-0000-1200-0014"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qianxue Bai","raw_affiliation_strings":["School of Mathematics and Science, Southwest University of Science and Technology, Mianyang, Sichuan, China"],"raw_orcid":"https://orcid.org/0009-0000-1200-0014","affiliations":[{"raw_affiliation_string":"School of Mathematics and Science, Southwest University of Science and Technology, Mianyang, Sichuan, China","institution_ids":["https://openalex.org/I1297991670"]}]},{"author_position":"last","author":{"id":null,"display_name":"Yi Gao","orcid":"https://orcid.org/0009-0009-5089-2696"},"institutions":[{"id":"https://openalex.org/I1297991670","display_name":"Southwest University of Science and Technology","ror":"https://ror.org/04d996474","country_code":"CN","type":"education","lineage":["https://openalex.org/I1297991670"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Gao","raw_affiliation_strings":["School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, Sichuan, China"],"raw_orcid":"https://orcid.org/0009-0009-5089-2696","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang, Sichuan, China","institution_ids":["https://openalex.org/I1297991670"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1297991670"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27903071,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"568","last_page":"572"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9948999881744385,"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/T10524","display_name":"Traffic control and management","score":0.9896000027656555,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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":0.579146146774292},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.45233628153800964},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.4390125274658203},{"id":"https://openalex.org/keywords/decision-model","display_name":"Decision model","score":0.42834270000457764},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.41967421770095825},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17750799655914307},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.16679811477661133},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07650145888328552}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.579146146774292},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.45233628153800964},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.4390125274658203},{"id":"https://openalex.org/C59594135","wikidata":"https://www.wikidata.org/wiki/Q5249242","display_name":"Decision model","level":2,"score":0.42834270000457764},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.41967421770095825},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17750799655914307},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.16679811477661133},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07650145888328552},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3716895.3716996","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3716895.3716996","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Artificial Intelligence and Computer Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.75,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2028387080","https://openalex.org/W2064675550","https://openalex.org/W2900661018","https://openalex.org/W2911964244","https://openalex.org/W2947812485","https://openalex.org/W2951627131","https://openalex.org/W3088618883","https://openalex.org/W4200099066","https://openalex.org/W4205840441","https://openalex.org/W4213071512","https://openalex.org/W4323038078","https://openalex.org/W6861449601"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"City":[0],"managers":[1],"have":[2],"long":[3],"been":[4],"committed":[5],"to":[6,63,121],"improving":[7],"the":[8,31,108,123,126,131,144,148,151],"efficiency":[9],"of":[10,34,44,112,125,133,150],"transportation":[11,36],"systems":[12],"and":[13,42,55,66,95,110],"reducing":[14],"congestion,":[15],"which":[16,106,129],"makes":[17],"urban":[18,79],"traffic":[19,69,80],"flow":[20,70,81],"forecasting":[21,24,45],"crucial.":[22],"Current":[23],"methods":[25],"often":[26],"do":[27],"not":[28],"adequately":[29],"consider":[30],"combined":[32],"effects":[33],"different":[35],"modes,":[37],"resulting":[38],"in":[39,140],"limited":[40],"accuracy":[41,109,132],"usefulness":[43],"results.":[46],"To":[47],"address":[48],"this":[49,52,73,115,141],"problem,":[50],"first,":[51],"paper":[53,74,116,142],"constructs":[54],"provides":[56],"two":[57],"novel":[58,119],"customized":[59],"datasets":[60],"that":[61],"help":[62],"better":[64],"understand":[65],"model":[67],"real-world":[68],"dynamics.":[71],"Second,":[72],"proposes":[75],"a":[76,118],"method":[77,120,138],"for":[78,103],"prediction":[82],"based":[83],"on":[84],"multi-model":[85],"decision":[86,104],"fusion.":[87],"This":[88],"approach":[89],"fuses":[90],"traditional":[91],"machine":[92],"learning":[93,97],"models":[94,98],"deep":[96],"using":[99],"their":[100],"respective":[101],"strengths":[102],"making,":[105],"improves":[107,130],"reliability":[111],"predictions.":[113],"Finally,":[114],"adopts":[117],"enhance":[122],"stability":[124],"predicted":[127],"data,":[128],"LSTM":[134],"long-term":[135],"prediction.":[136],"The":[137],"proposed":[139],"shows":[143],"best":[145],"performance":[146],"through":[147],"comparison":[149],"baseline":[152],"method.":[153]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
