{"id":"https://openalex.org/W3160242795","doi":"https://doi.org/10.3233/jifs-189991","title":"Analyzing influencing factors of crash injury severity incorporating FARS data","display_name":"Analyzing influencing factors of crash injury severity incorporating FARS data","publication_year":2021,"publication_date":"2021-05-14","ids":{"openalex":"https://openalex.org/W3160242795","doi":"https://doi.org/10.3233/jifs-189991","mag":"3160242795"},"language":"en","primary_location":{"id":"doi:10.3233/jifs-189991","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-189991","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy 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/A5100624995","display_name":"Zhijian Zhang","orcid":"https://orcid.org/0000-0001-9880-4872"},"institutions":[{"id":"https://openalex.org/I13985625","display_name":"East China Jiaotong University","ror":"https://ror.org/05x2f1m38","country_code":"CN","type":"education","lineage":["https://openalex.org/I13985625"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhijian Zhang","raw_affiliation_strings":["School of Transportation and Logistics, East China Jiaotong University, Nanchang, Jiangxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Transportation and Logistics, East China Jiaotong University, Nanchang, Jiangxi, China","institution_ids":["https://openalex.org/I13985625"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020089097","display_name":"Yubin Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I13985625","display_name":"East China Jiaotong University","ror":"https://ror.org/05x2f1m38","country_code":"CN","type":"education","lineage":["https://openalex.org/I13985625"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yubin Jiang","raw_affiliation_strings":["School of Transportation and Logistics, East China Jiaotong University, Nanchang, Jiangxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Transportation and Logistics, East China Jiaotong University, Nanchang, Jiangxi, China","institution_ids":["https://openalex.org/I13985625"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100739499","display_name":"Zhijun Chen","orcid":"https://orcid.org/0000-0002-0992-2656"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]},{"id":"https://openalex.org/I4210127216","display_name":"Ministry of Transport","ror":"https://ror.org/031wq1t38","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhijun Chen","raw_affiliation_strings":["Engineering Research Center for Transportation Safety, Ministry of Education, Wuhan, Hubei, China","Intelligent Transport Systems Research Center, Wuhan University of Technology, Wuhan, Hubei, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Engineering Research Center for Transportation Safety, Ministry of Education, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I4210127216"]},{"raw_affiliation_string":"Intelligent Transport Systems Research Center, Wuhan University of Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032489133","display_name":"Yubing Xiong","orcid":null},"institutions":[{"id":"https://openalex.org/I13985625","display_name":"East China Jiaotong University","ror":"https://ror.org/05x2f1m38","country_code":"CN","type":"education","lineage":["https://openalex.org/I13985625"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yubing Xiong","raw_affiliation_strings":["School of Transportation and Logistics, East China Jiaotong University, Nanchang, Jiangxi, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Transportation and Logistics, East China Jiaotong University, Nanchang, Jiangxi, China","institution_ids":["https://openalex.org/I13985625"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100739499"],"corresponding_institution_ids":["https://openalex.org/I196699116","https://openalex.org/I4210127216"],"apc_list":null,"apc_paid":null,"fwci":0.5001,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.62608629,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"41","issue":"4","first_page":"5053","last_page":"5063"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10370","display_name":"Traffic and Road Safety","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/T10298","display_name":"Urban Transport and Accessibility","score":0.9858999848365784,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9811999797821045,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/multinomial-logistic-regression","display_name":"Multinomial logistic regression","score":0.8305887579917908},{"id":"https://openalex.org/keywords/crash","display_name":"Crash","score":0.7424481511116028},{"id":"https://openalex.org/keywords/bayesian-network","display_name":"Bayesian network","score":0.5588027238845825},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5208964347839355},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5081305503845215},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.5002050399780273},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4866372048854828},{"id":"https://openalex.org/keywords/poison-control","display_name":"Poison control","score":0.4633173942565918},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.3707144856452942},{"id":"https://openalex.org/keywords/environmental-health","display_name":"Environmental health","score":0.26810503005981445},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.24379625916481018},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1976478099822998},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.17418819665908813},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15782469511032104}],"concepts":[{"id":"https://openalex.org/C117568660","wikidata":"https://www.wikidata.org/wiki/Q1650843","display_name":"Multinomial logistic regression","level":2,"score":0.8305887579917908},{"id":"https://openalex.org/C183469790","wikidata":"https://www.wikidata.org/wiki/Q333501","display_name":"Crash","level":2,"score":0.7424481511116028},{"id":"https://openalex.org/C33724603","wikidata":"https://www.wikidata.org/wiki/Q812540","display_name":"Bayesian network","level":2,"score":0.5588027238845825},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5208964347839355},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5081305503845215},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.5002050399780273},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4866372048854828},{"id":"https://openalex.org/C3017944768","wikidata":"https://www.wikidata.org/wiki/Q1450463","display_name":"Poison control","level":2,"score":0.4633173942565918},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.3707144856452942},{"id":"https://openalex.org/C99454951","wikidata":"https://www.wikidata.org/wiki/Q932068","display_name":"Environmental health","level":1,"score":0.26810503005981445},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.24379625916481018},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1976478099822998},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.17418819665908813},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15782469511032104},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/jifs-189991","is_oa":false,"landing_page_url":"https://doi.org/10.3233/jifs-189991","pdf_url":null,"source":{"id":"https://openalex.org/S179157397","display_name":"Journal of Intelligent & Fuzzy Systems","issn_l":"1064-1246","issn":["1064-1246","1875-8967"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Intelligent & Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.8600000143051147}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1050827452","https://openalex.org/W1846810705","https://openalex.org/W1980746151","https://openalex.org/W1998443375","https://openalex.org/W2027130787","https://openalex.org/W2039357427","https://openalex.org/W2042744865","https://openalex.org/W2051657664","https://openalex.org/W2077907477","https://openalex.org/W2084395525","https://openalex.org/W2099816914","https://openalex.org/W2409399929","https://openalex.org/W2513806877","https://openalex.org/W2516461418","https://openalex.org/W2794970226","https://openalex.org/W2804382304","https://openalex.org/W2886576602","https://openalex.org/W2895212257","https://openalex.org/W2936686278","https://openalex.org/W2969194299","https://openalex.org/W2981449380","https://openalex.org/W3008879069","https://openalex.org/W3008883625","https://openalex.org/W4242732037"],"related_works":["https://openalex.org/W2494119046","https://openalex.org/W2026516036","https://openalex.org/W626940945","https://openalex.org/W1506113033","https://openalex.org/W2369306031","https://openalex.org/W375763875","https://openalex.org/W2040826996","https://openalex.org/W2111579573","https://openalex.org/W120748129","https://openalex.org/W2061344455"],"abstract_inverted_index":{"The":[0,55,103,124,148,190],"purpose":[1],"of":[2,12,21,27,63,93,110,192,249,256],"this":[3,44],"study":[4],"is":[5,119,133,199,237],"to":[6,74,87,215,228,277,284,290],"deeply":[7],"analyze":[8,75],"the":[9,19,24,28,46,61,76,91,97,107,111,136,145,155,254,280],"influencing":[10,79],"factors":[11,156],"drivers\u2019":[13,158],"traffic":[14,35],"accident":[15,36],"casualties":[16],"and":[17,49,67,81,89,115,121,139,210,220,234,240,266,272],"reduce":[18],"occurrence":[20],"casualties.":[22],"From":[23],"FARS":[25],"database":[26],"National":[29],"Highway":[30],"Safety":[31],"Administration":[32],"(NHTSA),":[33],"93248":[34],"data":[37],"were":[38],"extracted":[39],"as":[40,226,288],"analysis":[41],"samples.":[42],"On":[43],"basis,":[45],"Bayesian":[47,70,112,125],"network":[48,113,126],"multinomial":[50,82,116,149],"logit":[51,83,117,150],"model":[52,57,64,114,118,151],"are":[53,72,85,141,180,207,269],"established.":[54],"constructed":[56],"was":[58],"tested":[59],"from":[60],"perspective":[62],"prediction":[65,108],"accuracy":[66,109],"variables":[68,95],"importance.":[69],"networks":[71],"used":[73,86],"interrelationships":[77],"among":[78],"factors,":[80,138],"models":[84],"compare":[88],"evaluate":[90],"impact":[92],"different":[94,101],"on":[96],"injury":[98,131,177,188,218,222,231,261,267],"severity":[99,132,219,223,265,268],"under":[100],"circumstances.":[102],"results":[104],"show":[105],"that:":[106],"64.57%":[120],"65.97%,":[122],"respectively.":[123,243],"reference":[127],"analyses":[128,152],"indicate":[129,153],"that":[130,154],"affected":[134],"by":[135,195],"crash":[137,168,186,258],"there":[140],"various":[142,146],"interactions":[143],"between":[144],"factors.":[147],"including":[157],"age,":[159],"female":[160],"driver,":[161],"rural":[162],"roads,":[163],"drunk":[164,202,204],"driving,":[165,167,203],"drug":[166,196,235],"time,":[169],"side":[170],"collision":[171],"accident,":[172],"etc.":[173,294],"could":[174],"significantly":[175],"increase":[176],"severity.":[178],"Airbags":[179],"more":[181,213,275],"effective":[182],"in":[183,224],"reducing":[184],"fatal":[185,221,257],"than":[187,201,260],"crash.":[189,262],"probability":[191],"accidents":[193],"caused":[194],"driving":[197,205,236],"drivers":[198,206],"greater":[200],"1.79":[208],"times":[209,212,239,271,274],"2.34":[211],"likely":[214,276],"suffer":[216],"an":[217],"crashes":[225],"compared":[227,289],"a":[229],"no":[230,291],"severity,":[232],"respectively,":[233,293],"1.93":[238],"2.6":[241],"times,":[242],"Seat":[244],"belts":[245],"may":[246],"avoid":[247],"92.2%":[248],"fatalities.":[250],"Roadside":[251],"guardrail":[252],"reduces":[253],"incidence":[255],"better":[259],"Fatal":[263],"injuries":[264],"1.124":[270],"1.141":[273],"occur":[278],"during":[279],"0":[281],":":[282,286],"00":[283,287],"6":[285],"injuries,":[292]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T08:27:34.040176","created_date":"2025-10-10T00:00:00"}