{"id":"https://openalex.org/W4308080993","doi":"https://doi.org/10.1109/itsc55140.2022.9922491","title":"A Fuzzy-based Convolutional LSTM Network Approach for Citywide Traffic Flow Prediction","display_name":"A Fuzzy-based Convolutional LSTM Network Approach for Citywide Traffic Flow Prediction","publication_year":2022,"publication_date":"2022-10-08","ids":{"openalex":"https://openalex.org/W4308080993","doi":"https://doi.org/10.1109/itsc55140.2022.9922491"},"language":"en","primary_location":{"id":"doi:10.1109/itsc55140.2022.9922491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc55140.2022.9922491","pdf_url":null,"source":{"id":"https://openalex.org/S4363607737","display_name":"2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5073885078","display_name":"Huiyun Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huiyun Yu","raw_affiliation_strings":["Tongji University,Ministry of Education, Key Laboratory of Embedded System and Service Computing,Shanghai,China,200092"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tongji University,Ministry of Education, Key Laboratory of Embedded System and Service Computing,Shanghai,China,200092","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101610027","display_name":"Qi Zheng","orcid":"https://orcid.org/0000-0001-6879-8256"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Zheng","raw_affiliation_strings":["Tongji University,Ministry of Education, Key Laboratory of Embedded System and Service Computing,Shanghai,China,200092"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tongji University,Ministry of Education, Key Laboratory of Embedded System and Service Computing,Shanghai,China,200092","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064219568","display_name":"Shuyun Qian","orcid":null},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuyun Qian","raw_affiliation_strings":["Tongji University,Ministry of Education, Key Laboratory of Embedded System and Service Computing,Shanghai,China,200092"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tongji University,Ministry of Education, Key Laboratory of Embedded System and Service Computing,Shanghai,China,200092","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048067916","display_name":"Yaying Zhang","orcid":"https://orcid.org/0000-0001-9552-3274"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaying Zhang","raw_affiliation_strings":["Tongji University,Ministry of Education, Key Laboratory of Embedded System and Service Computing,Shanghai,China,200092"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tongji University,Ministry of Education, Key Laboratory of Embedded System and Service Computing,Shanghai,China,200092","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":1.5608,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.81812523,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3360","last_page":"3367"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"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":1.0,"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":0.9929999709129333,"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":0.9922999739646912,"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":0.7421192526817322},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.733993649482727},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6573961973190308},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6349934339523315},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.6076918244361877},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.605269193649292},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.5783872604370117},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5606003403663635},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.517125129699707},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.44589874148368835},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4354253113269806},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.41305121779441833},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12866342067718506},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.06214055418968201}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7421192526817322},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.733993649482727},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6573961973190308},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6349934339523315},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.6076918244361877},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.605269193649292},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.5783872604370117},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5606003403663635},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.517125129699707},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.44589874148368835},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4354253113269806},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.41305121779441833},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12866342067718506},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.06214055418968201},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"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/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc55140.2022.9922491","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc55140.2022.9922491","pdf_url":null,"source":{"id":"https://openalex.org/S4363607737","display_name":"2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.7300000190734863,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G3557101512","display_name":null,"funder_award_id":"2018YFB2100800","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1485009520","https://openalex.org/W1522301498","https://openalex.org/W1967696505","https://openalex.org/W2004353783","https://openalex.org/W2074883049","https://openalex.org/W2086482048","https://openalex.org/W2095705004","https://openalex.org/W2097288650","https://openalex.org/W2112738128","https://openalex.org/W2149914169","https://openalex.org/W2150010190","https://openalex.org/W2156060469","https://openalex.org/W2169990839","https://openalex.org/W2417420127","https://openalex.org/W2528639018","https://openalex.org/W2575125657","https://openalex.org/W2624190409","https://openalex.org/W2756203131","https://openalex.org/W2793820729","https://openalex.org/W2808011586","https://openalex.org/W2808721728","https://openalex.org/W2901504064","https://openalex.org/W2946170292","https://openalex.org/W2964319113","https://openalex.org/W3102918078","https://openalex.org/W3103720336","https://openalex.org/W4396952261","https://openalex.org/W6628877408","https://openalex.org/W6631190155","https://openalex.org/W6674330103","https://openalex.org/W6686207219"],"related_works":["https://openalex.org/W4327499916","https://openalex.org/W4311257506","https://openalex.org/W2337926734","https://openalex.org/W4319994054","https://openalex.org/W2963958939","https://openalex.org/W4320802194","https://openalex.org/W2799614062","https://openalex.org/W3173182854","https://openalex.org/W4361732122","https://openalex.org/W4200507944"],"abstract_inverted_index":{"Citywide":[0],"traffic":[1,25,60,109],"flow":[2,26,61],"prediction":[3,62],"is":[4,30,52,70,90,101],"of":[5,58,87,95,108,129],"great":[6],"importance":[7],"to":[8,54,103],"intelligent":[9],"transportation":[10],"systems":[11],"and":[12,34,99,116],"smart":[13],"cities.":[14],"Although":[15],"many":[16],"deep":[17,28],"learning":[18,29,77],"methods":[19],"have":[20],"been":[21],"applied":[22],"for":[23],"citywide":[24,59],"prediction,":[27],"a":[31,44,71,79,123],"deterministic":[32],"representation":[33],"sheds":[35],"little":[36],"light":[37],"on":[38,122],"data":[39,65,88],"uncertainty.":[40],"In":[41],"this":[42],"paper,":[43],"fuzzy-based":[45],"convolutional":[46,80],"LSTM":[47,81],"neural":[48,82,97],"network":[49,83],"(FConvLSTM)":[50],"method":[51],"proposed":[53],"improve":[55],"the":[56,93,105,127,130],"accuracy":[57],"by":[63],"taking":[64],"uncertainty":[66,89],"into":[67],"consideration.":[68],"FConvLSTM":[69,131],"hybrid":[72],"model":[73],"which":[74,111],"combines":[75],"fuzzy":[76,96],"with":[78,92],"(ConvLSTM).":[84],"The":[85],"impact":[86],"lessened":[91],"help":[94],"networks":[98],"ConvLSTM":[100],"adopted":[102],"explore":[104],"spatio-temporal":[106],"characteristics":[107],"data,":[110],"can":[112],"learn":[113],"spatial":[114],"dependencies":[115,118],"temporal":[117],"jointly.":[119],"Experimental":[120],"results":[121],"real":[124],"dataset":[125],"verify":[126],"outperformance":[128],"method.":[132]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}