{"id":"https://openalex.org/W7160826703","doi":"https://doi.org/10.1109/access.2026.3691827","title":"An Enhanced Cost-Complexity Pruning (CCP) Approach for Analyzing Four-Level Traffic Accident Severity: A Multivariate Data Perspective","display_name":"An Enhanced Cost-Complexity Pruning (CCP) Approach for Analyzing Four-Level Traffic Accident Severity: A Multivariate Data Perspective","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7160826703","doi":"https://doi.org/10.1109/access.2026.3691827"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3691827","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3691827","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3691827","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012516689","display_name":"Bo Cao","orcid":"https://orcid.org/0000-0002-9235-859X"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Bo Cao","raw_affiliation_strings":["School of Economics and Management, Xidian University, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0009-0006-3137-6395","affiliations":[{"raw_affiliation_string":"School of Economics and Management, Xidian University, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135905808","display_name":"Ge Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210130954","display_name":"China Institute Of Communications","ror":"https://ror.org/0395ve714","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210130954"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ge Chen","raw_affiliation_strings":["Shaanxi College of Communications Technology, Xi&#x2019;an, China"],"raw_orcid":"https://orcid.org/0009-0005-9858-9486","affiliations":[{"raw_affiliation_string":"Shaanxi College of Communications Technology, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I4210130954"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054094650","display_name":"Xinyu He","orcid":"https://orcid.org/0000-0002-2519-7650"},"institutions":[{"id":"https://openalex.org/I148099405","display_name":"Xi'an University of Architecture and Technology","ror":"https://ror.org/04v2j2k71","country_code":"CN","type":"education","lineage":["https://openalex.org/I148099405"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinyu He","raw_affiliation_strings":["Huaqing College, Xi&#x2019;an University of Architecture and Technology, Xi&#x2019;an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Huaqing College, Xi&#x2019;an University of Architecture and Technology, Xi&#x2019;an, China","institution_ids":["https://openalex.org/I148099405"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012516689"],"corresponding_institution_ids":["https://openalex.org/I149594827"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.88324719,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"71275","last_page":"71294"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.44850000739097595,"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":0.44850000739097595,"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/T11357","display_name":"Risk and Safety Analysis","score":0.09000000357627869,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10524","display_name":"Traffic control and management","score":0.04410000145435333,"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/perspective","display_name":"Perspective (graphical)","score":0.6924999952316284},{"id":"https://openalex.org/keywords/multivariate-statistics","display_name":"Multivariate statistics","score":0.6244000196456909},{"id":"https://openalex.org/keywords/pruning","display_name":"Pruning","score":0.5961999893188477},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4876999855041504},{"id":"https://openalex.org/keywords/traffic-accident","display_name":"Traffic accident","score":0.4002000093460083},{"id":"https://openalex.org/keywords/accident","display_name":"Accident (philosophy)","score":0.3944999873638153}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7788000106811523},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.6924999952316284},{"id":"https://openalex.org/C161584116","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate statistics","level":2,"score":0.6244000196456909},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6061999797821045},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.5961999893188477},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5922999978065491},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4876999855041504},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4244999885559082},{"id":"https://openalex.org/C2989506057","wikidata":"https://www.wikidata.org/wiki/Q9687","display_name":"Traffic accident","level":2,"score":0.4002000093460083},{"id":"https://openalex.org/C2780289543","wikidata":"https://www.wikidata.org/wiki/Q424630","display_name":"Accident (philosophy)","level":2,"score":0.3944999873638153},{"id":"https://openalex.org/C2985695025","wikidata":"https://www.wikidata.org/wiki/Q4323994","display_name":"Road traffic","level":2,"score":0.3037000000476837},{"id":"https://openalex.org/C38180746","wikidata":"https://www.wikidata.org/wiki/Q1952580","display_name":"Multivariate analysis","level":2,"score":0.27889999747276306},{"id":"https://openalex.org/C3020028006","wikidata":"https://www.wikidata.org/wiki/Q9158","display_name":"Electronic mail","level":2,"score":0.2703000009059906},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2596000134944916},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2590999901294708}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3691827","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3691827","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1368661b323144b99960067ed58b0c59","is_oa":true,"landing_page_url":"https://doaj.org/article/1368661b323144b99960067ed58b0c59","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 71275-71294 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3691827","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3691827","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","score":0.6057877540588379,"display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"study":[1],"employs":[2],"Cost-Complexity":[3],"Pruning":[4],"(CCP)":[5],"decision":[6],"trees":[7],"to":[8],"investigate":[9],"determinants":[10],"of":[11],"four-level":[12],"traffic":[13,151],"accident":[14,107],"severity":[15,108,129],"(minor,":[16],"moderate,":[17],"major,":[18],"and":[19,33,39,61,72,78,91,94,99,122,134,154],"highly":[20],"severe).":[21],"We":[22],"analyze":[23],"32":[24],"variables":[25],"covering":[26],"occupant":[27,135],"characteristics,":[28,32],"vehicle":[29,132],"attributes,":[30],"crash":[31,118],"roadway/environment":[34],"conditions.":[35],"To":[36,75],"mitigate":[37],"inefficiency":[38],"overfitting":[40],"in":[41,141],"standard":[42],"CCP-based":[43],"trees,":[44],"we":[45,82],"propose":[46],"an":[47,63],"enhanced":[48],"CCP":[49],"pipeline":[50],"with":[51,88,117],"two":[52],"optimizations:":[53],"(i)":[54],"training-data":[55],"restriction":[56],"via":[57],"wrapper-based":[58],"attribute":[59],"selection,":[60],"(ii)":[62],"S-score\u2013guided":[64],"pruning":[65],"rule":[66],"that":[67,105],"jointly":[68],"considers":[69],"leaf":[70],"accuracy":[71],"node":[73],"coverage.":[74],"ensure":[76],"reproducibility":[77],"reliable":[79],"generalization":[80],"assessment,":[81],"report":[83],"a":[84],"stratified":[85],"evaluation":[86],"protocol":[87],"baseline":[89],"comparisons":[90],"ablation":[92],"settings,":[93],"summarize":[95],"performance":[96],"using":[97],"macro-averaged":[98],"imbalance-robust":[100],"metrics.":[101],"The":[102],"findings":[103],"reveal":[104],"as":[106],"increases,":[109],"the":[110],"associated":[111],"factor":[112],"patterns":[113],"become":[114,138],"more":[115],"complex,":[116],"configuration":[119],"(collision":[120],"location":[121],"impact":[123],"direction)":[124],"remaining":[125],"influential":[126],"across":[127],"all":[128],"levels,":[130],"while":[131],"protection":[133],"restraint":[136],"features":[137],"increasingly":[139],"prominent":[140],"high-severity":[142],"outcomes.":[143],"These":[144],"results":[145],"provide":[146],"actionable":[147],"evidence":[148],"for":[149],"targeted":[150],"safety":[152],"management":[153],"injury":[155],"prevention.":[156]},"counts_by_year":[],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2026-05-12T00:00:00"}
