{"id":"https://openalex.org/W7128594133","doi":"https://doi.org/10.3390/systems14020190","title":"Inferring Spatiotemporal Propagation Strength and Mining Influential Patterns in Urban Traffic Network","display_name":"Inferring Spatiotemporal Propagation Strength and Mining Influential Patterns in Urban Traffic Network","publication_year":2026,"publication_date":"2026-02-10","ids":{"openalex":"https://openalex.org/W7128594133","doi":"https://doi.org/10.3390/systems14020190"},"language":"en","primary_location":{"id":"doi:10.3390/systems14020190","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14020190","pdf_url":"https://www.mdpi.com/2079-8954/14/2/190/pdf?version=1770774866","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2079-8954/14/2/190/pdf?version=1770774866","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125610190","display_name":"Wenbo Zhang","orcid":null},"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":true,"raw_author_name":"Wenbo Zhang","raw_affiliation_strings":["School of Transportation, Southeast University, 2 Southeast University Road, Nanjing 211189, China"],"raw_orcid":"https://orcid.org/0000-0003-2002-7852","affiliations":[{"raw_affiliation_string":"School of Transportation, Southeast University, 2 Southeast University Road, Nanjing 211189, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125620456","display_name":"Bo Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I223532165","display_name":"University of Utah","ror":"https://ror.org/03r0ha626","country_code":"US","type":"education","lineage":["https://openalex.org/I223532165"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Wang","raw_affiliation_strings":["Department of Civil and Environmental Engineering, The University of Utah, 110 Central Campus Drive, Salt Lake City, UT 84112, USA"],"raw_orcid":"https://orcid.org/0009-0004-0168-5803","affiliations":[{"raw_affiliation_string":"Department of Civil and Environmental Engineering, The University of Utah, 110 Central Campus Drive, Salt Lake City, UT 84112, USA","institution_ids":["https://openalex.org/I223532165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026841514","display_name":"Yikai Fang","orcid":null},"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":"Yikai Fang","raw_affiliation_strings":["School of Transportation, Southeast University, 2 Southeast University Road, Nanjing 211189, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Transportation, Southeast University, 2 Southeast University Road, Nanjing 211189, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125604516","display_name":"Shangyu Li","orcid":null},"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":"Shangyu Li","raw_affiliation_strings":["School of Transportation, Southeast University, 2 Southeast University Road, Nanjing 211189, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Transportation, Southeast University, 2 Southeast University Road, Nanjing 211189, China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5125610190"],"corresponding_institution_ids":["https://openalex.org/I76569877"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1732},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1732},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.29442111,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":"2","first_page":"190","last_page":"190"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9171000123023987,"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":0.9171000123023987,"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/T10524","display_name":"Traffic control and management","score":0.030300000682473183,"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"}},{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.005200000014156103,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/traceability","display_name":"Traceability","score":0.7190999984741211},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5471000075340271},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4943999946117401},{"id":"https://openalex.org/keywords/clustering-coefficient","display_name":"Clustering coefficient","score":0.4828999936580658},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.4797999858856201},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.45329999923706055},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.45179998874664307},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.39309999346733093}],"concepts":[{"id":"https://openalex.org/C153876917","wikidata":"https://www.wikidata.org/wiki/Q899704","display_name":"Traceability","level":2,"score":0.7190999984741211},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.609499990940094},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5742999911308289},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5471000075340271},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4943999946117401},{"id":"https://openalex.org/C22047676","wikidata":"https://www.wikidata.org/wiki/Q898680","display_name":"Clustering coefficient","level":3,"score":0.4828999936580658},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.4797999858856201},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.45329999923706055},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.45179998874664307},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.39309999346733093},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.35499998927116394},{"id":"https://openalex.org/C32946077","wikidata":"https://www.wikidata.org/wiki/Q618079","display_name":"Network analysis","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.3109999895095825},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.29760000109672546},{"id":"https://openalex.org/C199845137","wikidata":"https://www.wikidata.org/wiki/Q145490","display_name":"Network topology","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2863999903202057},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.2838999927043915},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.2741999924182892},{"id":"https://openalex.org/C2781317605","wikidata":"https://www.wikidata.org/wiki/Q7832483","display_name":"Traffic analysis","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C114809511","wikidata":"https://www.wikidata.org/wiki/Q1412924","display_name":"Flow network","level":2,"score":0.26010000705718994},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.2533999979496002},{"id":"https://openalex.org/C125112378","wikidata":"https://www.wikidata.org/wiki/Q176640","display_name":"Randomness","level":2,"score":0.25040000677108765}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/systems14020190","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14020190","pdf_url":"https://www.mdpi.com/2079-8954/14/2/190/pdf?version=1770774866","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1591218fcfa74ba484a1b7ac72187906","is_oa":true,"landing_page_url":"https://doaj.org/article/1591218fcfa74ba484a1b7ac72187906","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Systems, Vol 14, Iss 2, p 190 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/systems14020190","is_oa":true,"landing_page_url":"https://doi.org/10.3390/systems14020190","pdf_url":"https://www.mdpi.com/2079-8954/14/2/190/pdf?version=1770774866","source":{"id":"https://openalex.org/S4210219410","display_name":"Systems","issn_l":"2079-8954","issn":["2079-8954"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8336566686630249,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7128594133.pdf","grobid_xml":"https://content.openalex.org/works/W7128594133.grobid-xml"},"referenced_works_count":15,"referenced_works":["https://openalex.org/W2041782669","https://openalex.org/W2073209910","https://openalex.org/W2080180737","https://openalex.org/W2117618130","https://openalex.org/W2178225550","https://openalex.org/W2257812508","https://openalex.org/W2516039095","https://openalex.org/W2897639833","https://openalex.org/W4317933138","https://openalex.org/W4378364371","https://openalex.org/W4385343305","https://openalex.org/W4388128415","https://openalex.org/W4412520004","https://openalex.org/W4413480946","https://openalex.org/W4413835821"],"related_works":[],"abstract_inverted_index":{"Understanding":[0],"the":[1,25,34,41,44,69,97,115,120,155,166],"propagation":[2,26,64,146],"interactions":[3,49],"among":[4,50,66],"intersections":[5,29,67,95],"in":[6,75,88,144],"city":[7],"road":[8,90],"networks":[9],"and":[10,21,40,68,123,160,175],"uncovering":[11],"their":[12],"traceability":[13,56,86,130,179],"patterns":[14,57,87,180],"is":[15,30],"vital":[16],"for":[17,84],"proactive":[18],"traffic":[19,38,139],"management":[20],"control.":[22],"However,":[23],"measuring":[24],"strength":[27,147],"between":[28],"difficult":[31],"due":[32],"to":[33,71,113,127,149],"dynamic":[35],"nature":[36],"of":[37,62,119,158],"flow":[39],"interference":[42],"at":[43],"network":[45,76],"level":[46],"caused":[47],"by":[48,182],"many":[51],"nearby":[52],"intersections.":[53],"Additionally,":[54],"mining":[55],"requires":[58],"a":[59,81],"comprehensive":[60],"representation":[61],"complex":[63],"influences":[65],"ability":[70],"detect":[72],"subtle":[73],"changes":[74],"structure.":[77],"This":[78],"study":[79,167],"introduces":[80],"detailed":[82],"framework":[83],"extracting":[85],"urban":[89],"networks.":[91],"It":[92],"identifies":[93],"high-impact":[94,159,161],"using":[96,137],"mean":[98],"excess":[99],"function,":[100],"constructs":[101],"an":[102],"interaction":[103,121,171],"graph":[104,110],"with":[105],"these":[106,183],"critical":[107],"nodes,":[108],"applies":[109],"structural":[111],"entropy":[112],"describe":[114],"global":[116],"topological":[117],"features":[118],"graph,":[122],"uses":[124],"k-means":[125],"clustering":[126],"classify":[128],"different":[129],"patterns.":[131],"The":[132],"proposed":[133],"method":[134],"was":[135],"validated":[136],"real-world":[138],"data,":[140],"showing":[141],"superior":[142],"performance":[143],"estimating":[145],"compared":[148],"benchmark":[150],"models.":[151],"Kolmogorov\u2013Smirnov":[152],"tests":[153],"confirmed":[154],"statistical":[156],"reliability":[157],"intersection":[162],"identification":[163],"results.":[164],"Furthermore,":[165],"identified":[168],"four":[169,177],"core":[170],"structures\u2014chain,":[172],"collider,":[173],"fork,":[174],"circle\u2014and":[176],"representative":[178],"formed":[181],"structures.":[184]},"counts_by_year":[],"updated_date":"2026-03-10T14:07:55.174380","created_date":"2026-02-11T00:00:00"}