{"id":"https://openalex.org/W4399939387","doi":"https://doi.org/10.1109/tii.2024.3413355","title":"Development of an Automated Global Crash Prediction Model With Adaptive Feature Selection of Deep Neural Networks","display_name":"Development of an Automated Global Crash Prediction Model With Adaptive Feature Selection of Deep Neural Networks","publication_year":2024,"publication_date":"2024-06-24","ids":{"openalex":"https://openalex.org/W4399939387","doi":"https://doi.org/10.1109/tii.2024.3413355"},"language":"en","primary_location":{"id":"doi:10.1109/tii.2024.3413355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2024.3413355","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Informatics","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/A5079515172","display_name":"Guangyuan Pan","orcid":"https://orcid.org/0000-0003-0115-6659"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guangyuan Pan","raw_affiliation_strings":["School of Automation and Electrical Engineering, Linyi University, Linyi, China"],"raw_orcid":"https://orcid.org/0000-0003-0115-6659","affiliations":[{"raw_affiliation_string":"School of Automation and Electrical Engineering, Linyi University, Linyi, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108028771","display_name":"Gongming Wang","orcid":"https://orcid.org/0000-0002-8124-2890"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gongming Wang","raw_affiliation_strings":["Department of Information, Beijing University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8124-2890","affiliations":[{"raw_affiliation_string":"Department of Information, Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100645136","display_name":"Hao Wei","orcid":"https://orcid.org/0009-0005-6053-4455"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wei","raw_affiliation_strings":["School of Automation and Electrical Engineering, Linyi University, Linyi, China"],"raw_orcid":"https://orcid.org/0009-0005-6053-4455","affiliations":[{"raw_affiliation_string":"School of Automation and Electrical Engineering, Linyi University, Linyi, China","institution_ids":["https://openalex.org/I15823474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055102556","display_name":"Qili Chen","orcid":"https://orcid.org/0000-0002-9194-3236"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qili Chen","raw_affiliation_strings":["College of Automation, Beijing Information Science and Technology University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9194-3236","affiliations":[{"raw_affiliation_string":"College of Automation, Beijing Information Science and Technology University, Beijing, China","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064606741","display_name":"Ancai Zhang","orcid":"https://orcid.org/0000-0003-3776-7945"},"institutions":[{"id":"https://openalex.org/I15823474","display_name":"Linyi University","ror":"https://ror.org/01knv0402","country_code":"CN","type":"education","lineage":["https://openalex.org/I15823474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ancai Zhang","raw_affiliation_strings":["School of Automation and Electrical Engineering, Linyi University, Linyi, China"],"raw_orcid":"https://orcid.org/0000-0003-3776-7945","affiliations":[{"raw_affiliation_string":"School of Automation and Electrical Engineering, Linyi University, Linyi, China","institution_ids":["https://openalex.org/I15823474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5079515172"],"corresponding_institution_ids":["https://openalex.org/I15823474"],"apc_list":null,"apc_paid":null,"fwci":0.2537,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.53046072,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"20","issue":"10","first_page":"12010","last_page":"12020"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.7267000079154968,"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":0.7267000079154968,"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/computer-science","display_name":"Computer science","score":0.6846399307250977},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6558812260627747},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6401179432868958},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6350380778312683},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.49229303002357483},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48622503876686096},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4846790134906769},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44321489334106445},{"id":"https://openalex.org/keywords/crash","display_name":"Crash","score":0.43706876039505005},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4301786720752716},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37031033635139465},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3644532263278961}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6846399307250977},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6558812260627747},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6401179432868958},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6350380778312683},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.49229303002357483},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48622503876686096},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4846790134906769},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44321489334106445},{"id":"https://openalex.org/C183469790","wikidata":"https://www.wikidata.org/wiki/Q333501","display_name":"Crash","level":2,"score":0.43706876039505005},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4301786720752716},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37031033635139465},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3644532263278961},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tii.2024.3413355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tii.2024.3413355","pdf_url":null,"source":{"id":"https://openalex.org/S184777250","display_name":"IEEE Transactions on Industrial Informatics","issn_l":"1551-3203","issn":["1551-3203","1941-0050"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Industrial Informatics","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3313990683","display_name":null,"funder_award_id":"61803193","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7498554848","display_name":null,"funder_award_id":"62103177","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W2576291079","https://openalex.org/W2743180505","https://openalex.org/W2897805291","https://openalex.org/W2904055553","https://openalex.org/W2908971902","https://openalex.org/W2940710818","https://openalex.org/W2958089299","https://openalex.org/W2965446359","https://openalex.org/W2978345223","https://openalex.org/W2997370631","https://openalex.org/W2997586231","https://openalex.org/W3005600385","https://openalex.org/W3013623116","https://openalex.org/W3013822684","https://openalex.org/W3032399050","https://openalex.org/W3040166285","https://openalex.org/W3041146978","https://openalex.org/W3085522432","https://openalex.org/W3090429194","https://openalex.org/W3100805595","https://openalex.org/W3110441058","https://openalex.org/W3167872037","https://openalex.org/W4213115640","https://openalex.org/W4213177737","https://openalex.org/W4386302335","https://openalex.org/W4386396760","https://openalex.org/W6790227089"],"related_works":["https://openalex.org/W2026516036","https://openalex.org/W626940945","https://openalex.org/W2040826996","https://openalex.org/W375763875","https://openalex.org/W2111579573","https://openalex.org/W120748129","https://openalex.org/W2061344455","https://openalex.org/W2744235150","https://openalex.org/W4386564352","https://openalex.org/W2952668426"],"abstract_inverted_index":{"To":[0],"construct":[1],"an":[2],"accurate":[3],"crash":[4],"prediction":[5],"model,":[6],"the":[7,19,29,40,78,101,124,128],"road":[8],"safety":[9,16],"performance":[10],"function":[11],"(SPF),":[12],"which":[13],"provides":[14],"a":[15,51,73,94],"guide":[17,99],"for":[18,100],"management":[20,102],"department,":[21],"is":[22,34,42,61],"often":[23],"used.":[24],"In":[25],"traditional":[26],"parametric":[27,57],"SPFs,":[28,58],"importance":[30,96],"of":[31,137],"traffic":[32],"features":[33],"calculated":[35],"using":[36,111],"analytic":[37],"expression,":[38],"but":[39,90],"model":[41,70,81,142],"inaccurate":[43],"and":[44,72,97,120,141],"low":[45],"in":[46,123,135],"generalization.":[47],"This":[48],"article":[49],"proposes":[50],"machine":[52],"learning-based":[53],"method":[54],"to":[55,104],"replace":[56],"this":[59,80],"framework":[60,130],"built":[62],"based":[63],"on":[64],"integrated":[65],"visual":[66],"feature":[67,95],"importance,":[68],"global":[69],"training,":[71],"structure":[74],"self-organizing":[75],"scheme.":[76],"From":[77],"analysis,":[79],"can":[82,91],"not":[83],"only":[84],"predict":[85],"multiregional":[86],"car":[87],"crashes":[88],"accurately":[89],"also":[92],"provide":[93],"selection":[98],"department":[103],"better":[105],"understand":[106],"it.":[107],"At":[108],"last,":[109],"experiments":[110],"real-world":[112],"data":[113],"collected":[114],"from":[115],"Highway":[116],"401":[117],"Ontario":[118],"Canada":[119],"several":[121],"highways":[122],"U.S.":[125],"show":[126],"that":[127],"proposed":[129],"outperformed":[131],"other":[132],"State-of-the-Art":[133],"models":[134],"terms":[136],"interpretability,":[138],"accuracy,":[139],"generalizability,":[140],"conciseness.":[143]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-12-26T23:08:49.675405","created_date":"2025-10-10T00:00:00"}
