{"id":"https://openalex.org/W2152239094","doi":"https://doi.org/10.1109/cso.2012.103","title":"A Mixed-Fractal Traffic Flow Model Whose Hurst Exponent Appears Crossover","display_name":"A Mixed-Fractal Traffic Flow Model Whose Hurst Exponent Appears Crossover","publication_year":2012,"publication_date":"2012-06-01","ids":{"openalex":"https://openalex.org/W2152239094","doi":"https://doi.org/10.1109/cso.2012.103","mag":"2152239094"},"language":"en","primary_location":{"id":"doi:10.1109/cso.2012.103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cso.2012.103","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 Fifth International Joint Conference on Computational Sciences and Optimization","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":"https://openalex.org/A5100360971","display_name":"Li Li","orcid":"https://orcid.org/0000-0001-5512-6629"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Li Li","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100765837","display_name":"Zhiheng Li","orcid":"https://orcid.org/0000-0002-1523-1114"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiheng Li","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100653787","display_name":"Yi Zhang","orcid":"https://orcid.org/0000-0001-5526-866X"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Zhang","raw_affiliation_strings":["Department of Automation, Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Department of Automation, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060774236","display_name":"Yudong Chen","orcid":"https://orcid.org/0000-0002-6416-5635"},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yudong Chen","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Texas, Austin, Austin, TX, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Texas, Austin, Austin, TX, USA","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100360971"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.4851,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.66211268,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"443","last_page":"447"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10591","display_name":"Theoretical and Computational Physics","score":0.9957000017166138,"subfield":{"id":"https://openalex.org/subfields/3104","display_name":"Condensed Matter Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hurst-exponent","display_name":"Hurst exponent","score":0.9657110571861267},{"id":"https://openalex.org/keywords/crossover","display_name":"Crossover","score":0.8919156193733215},{"id":"https://openalex.org/keywords/fractal","display_name":"Fractal","score":0.8102667331695557},{"id":"https://openalex.org/keywords/exponent","display_name":"Exponent","score":0.6388720273971558},{"id":"https://openalex.org/keywords/statistical-physics","display_name":"Statistical physics","score":0.5543926954269409},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5165256857872009},{"id":"https://openalex.org/keywords/flow","display_name":"Flow (mathematics)","score":0.5019316673278809},{"id":"https://openalex.org/keywords/detrended-fluctuation-analysis","display_name":"Detrended fluctuation analysis","score":0.4811374247074127},{"id":"https://openalex.org/keywords/traffic-flow","display_name":"Traffic flow (computer networking)","score":0.42944246530532837},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.34376564621925354},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27765485644340515},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.21472615003585815},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1699640452861786},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.16897019743919373},{"id":"https://openalex.org/keywords/mathematical-analysis","display_name":"Mathematical analysis","score":0.12289246916770935},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.10017931461334229},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.08100628852844238}],"concepts":[{"id":"https://openalex.org/C96835011","wikidata":"https://www.wikidata.org/wiki/Q1638718","display_name":"Hurst exponent","level":2,"score":0.9657110571861267},{"id":"https://openalex.org/C122507166","wikidata":"https://www.wikidata.org/wiki/Q628906","display_name":"Crossover","level":2,"score":0.8919156193733215},{"id":"https://openalex.org/C40636538","wikidata":"https://www.wikidata.org/wiki/Q81392","display_name":"Fractal","level":2,"score":0.8102667331695557},{"id":"https://openalex.org/C2780388253","wikidata":"https://www.wikidata.org/wiki/Q5421508","display_name":"Exponent","level":2,"score":0.6388720273971558},{"id":"https://openalex.org/C121864883","wikidata":"https://www.wikidata.org/wiki/Q677916","display_name":"Statistical physics","level":1,"score":0.5543926954269409},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5165256857872009},{"id":"https://openalex.org/C38349280","wikidata":"https://www.wikidata.org/wiki/Q1434290","display_name":"Flow (mathematics)","level":2,"score":0.5019316673278809},{"id":"https://openalex.org/C21689155","wikidata":"https://www.wikidata.org/wiki/Q2451452","display_name":"Detrended fluctuation analysis","level":3,"score":0.4811374247074127},{"id":"https://openalex.org/C207512268","wikidata":"https://www.wikidata.org/wiki/Q3074551","display_name":"Traffic flow (computer networking)","level":2,"score":0.42944246530532837},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.34376564621925354},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27765485644340515},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.21472615003585815},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1699640452861786},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.16897019743919373},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.12289246916770935},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.10017931461334229},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.08100628852844238},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cso.2012.103","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cso.2012.103","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 Fifth International Joint Conference on Computational Sciences and Optimization","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6100000143051147,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W656576684","https://openalex.org/W1499963479","https://openalex.org/W1525210873","https://openalex.org/W1607632979","https://openalex.org/W1972309850","https://openalex.org/W1975844205","https://openalex.org/W1978061253","https://openalex.org/W1985051501","https://openalex.org/W1989588625","https://openalex.org/W1994774729","https://openalex.org/W1995855693","https://openalex.org/W2009399065","https://openalex.org/W2047568005","https://openalex.org/W2048076057","https://openalex.org/W2061735971","https://openalex.org/W2081416540","https://openalex.org/W2095864287","https://openalex.org/W2102616700","https://openalex.org/W2105818147","https://openalex.org/W2120202031","https://openalex.org/W2121217657","https://openalex.org/W2134004786","https://openalex.org/W2143768661","https://openalex.org/W2148212971","https://openalex.org/W2150462633","https://openalex.org/W2156896296","https://openalex.org/W2157488135","https://openalex.org/W2164214015","https://openalex.org/W2170125123","https://openalex.org/W2171873915","https://openalex.org/W2252927647","https://openalex.org/W2485102757","https://openalex.org/W3009448230","https://openalex.org/W3105540635","https://openalex.org/W3123940430","https://openalex.org/W4246756383"],"related_works":["https://openalex.org/W4321505114","https://openalex.org/W2057384585","https://openalex.org/W2035064929","https://openalex.org/W2401810189","https://openalex.org/W2073997720","https://openalex.org/W2070565950","https://openalex.org/W2795419853","https://openalex.org/W2911012399","https://openalex.org/W2125635163","https://openalex.org/W2058567967"],"abstract_inverted_index":{"In":[0],"this":[1,83],"paper,":[2],"we":[3],"propose":[4],"a":[5,13,18],"new":[6],"traffic":[7,37,89],"flow":[8,38],"model,":[9],"aiming":[10],"to":[11],"provide":[12],"possible":[14],"explanation":[15],"and":[16,71,91],"meanwhile":[17],"useful":[19,86],"simulation":[20],"tool":[21],"for":[22,34],"the":[23,31,35,62,65],"multi-fractal":[24],"network":[25,88],"traffic.":[26],"It":[27],"is":[28,85],"shown":[29],"that":[30,82],"Hurst":[32,52,77],"exponent":[33],"mainline":[36],"will":[39],"appear":[40],"crossover":[41,55],"phenomena,":[42],"if":[43],"it":[44],"consists":[45],"of":[46],"several":[47],"self-similar":[48],"components":[49],"with":[50],"different":[51],"exponents.":[53,78],"Therefore,":[54],"phenomena":[56],"are":[57,68],"pervasive":[58],"in":[59,87],"practice,":[60],"since":[61],"inflows":[63],"from":[64],"branch":[66],"lines":[67],"usually":[69],"heterogenous":[70],"may":[72],"have":[73],"similar":[74],"yet":[75],"distinct":[76],"Our":[79],"results":[80],"indicate":[81],"model":[84],"modeling":[90],"simulation.":[92]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}