{"id":"https://openalex.org/W1967051566","doi":"https://doi.org/10.1080/18756891.2011.9727792","title":"Incident Duration Prediction Based on Latent Gaussian Naive Bayesian classifier","display_name":"Incident Duration Prediction Based on Latent Gaussian Naive Bayesian classifier","publication_year":2011,"publication_date":"2011-05-01","ids":{"openalex":"https://openalex.org/W1967051566","doi":"https://doi.org/10.1080/18756891.2011.9727792","mag":"1967051566"},"language":"en","primary_location":{"id":"doi:10.1080/18756891.2011.9727792","is_oa":true,"landing_page_url":"https://doi.org/10.1080/18756891.2011.9727792","pdf_url":null,"source":{"id":"https://openalex.org/S190680769","display_name":"International Journal of Computational Intelligence Systems","issn_l":"1875-6883","issn":["1875-6883","1875-6891"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1080/18756891.2011.9727792","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100324970","display_name":"Dawei Li","orcid":"https://orcid.org/0000-0003-1411-3260"},"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":"Dawei Li","raw_affiliation_strings":["School of Transportation , Southeast University , Nanjing , 210096 , P. R. China","School of Transportation, Southeast Univ., Nanjing 210096, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Transportation , Southeast University , Nanjing , 210096 , P. R. China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Transportation, Southeast Univ., Nanjing 210096, P.R. China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027912066","display_name":"Lin Cheng","orcid":"https://orcid.org/0000-0003-1617-0154"},"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":"Lin Cheng","raw_affiliation_strings":["School of Transportation , Southeast University , Nanjing , 210096 , P. R. China","School of Transportation, Southeast Univ., Nanjing 210096, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Transportation , Southeast University , Nanjing , 210096 , P. R. China","institution_ids":["https://openalex.org/I76569877"]},{"raw_affiliation_string":"School of Transportation, Southeast Univ., Nanjing 210096, P.R. China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020072375","display_name":"Jiangshan Ma","orcid":"https://orcid.org/0000-0003-3491-5527"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Jiangshan Ma","raw_affiliation_strings":["Department of Civil and Environmental Engineering , Tokyo Institute of Technology , Tokyo , 152-8552 , Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Civil and Environmental Engineering , Tokyo Institute of Technology , Tokyo , 152-8552 , Japan","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1390,"currency":"GBP","value_usd":1704},"apc_paid":{"value":1390,"currency":"GBP","value_usd":1704},"fwci":1.7025,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.85289838,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"4","issue":"3","first_page":"345","last_page":"352"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":1.0,"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":1.0,"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/T10698","display_name":"Transportation Planning and Optimization","score":0.9983999729156494,"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/T10370","display_name":"Traffic and Road Safety","score":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/log-normal-distribution","display_name":"Log-normal distribution","score":0.6531891226768494},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5648245811462402},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.5334109663963318},{"id":"https://openalex.org/keywords/duration","display_name":"Duration (music)","score":0.5236147046089172},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.43868350982666016},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4346330761909485},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.42981287837028503},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4287341237068176},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.34060126543045044},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2983933091163635},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.09756603837013245}],"concepts":[{"id":"https://openalex.org/C151620405","wikidata":"https://www.wikidata.org/wiki/Q826116","display_name":"Log-normal distribution","level":2,"score":0.6531891226768494},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5648245811462402},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.5334109663963318},{"id":"https://openalex.org/C112758219","wikidata":"https://www.wikidata.org/wiki/Q16038819","display_name":"Duration (music)","level":2,"score":0.5236147046089172},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.43868350982666016},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4346330761909485},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.42981287837028503},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4287341237068176},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.34060126543045044},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2983933091163635},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.09756603837013245},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/18756891.2011.9727792","is_oa":true,"landing_page_url":"https://doi.org/10.1080/18756891.2011.9727792","pdf_url":null,"source":{"id":"https://openalex.org/S190680769","display_name":"International Journal of Computational Intelligence Systems","issn_l":"1875-6883","issn":["1875-6883","1875-6891"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1080/18756891.2011.9727792","is_oa":true,"landing_page_url":"https://doi.org/10.1080/18756891.2011.9727792","pdf_url":null,"source":{"id":"https://openalex.org/S190680769","display_name":"International Journal of Computational Intelligence Systems","issn_l":"1875-6883","issn":["1875-6883","1875-6891"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Computational Intelligence Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1522168924","https://openalex.org/W1532791662","https://openalex.org/W1965036911","https://openalex.org/W1995840715","https://openalex.org/W2006840108","https://openalex.org/W2010039425","https://openalex.org/W2015040335","https://openalex.org/W2035481685","https://openalex.org/W2040794788","https://openalex.org/W2053882385","https://openalex.org/W2055292920","https://openalex.org/W2062922945","https://openalex.org/W2088796177","https://openalex.org/W2135310819","https://openalex.org/W2149477967","https://openalex.org/W2150010190","https://openalex.org/W2170684983","https://openalex.org/W2248155396","https://openalex.org/W2608724236","https://openalex.org/W2979006918","https://openalex.org/W2992519396"],"related_works":["https://openalex.org/W2348837382","https://openalex.org/W746329893","https://openalex.org/W4205872570","https://openalex.org/W4245971243","https://openalex.org/W2493033802","https://openalex.org/W1922805944","https://openalex.org/W4253588120","https://openalex.org/W2383732295","https://openalex.org/W4248716494","https://openalex.org/W3098004296"],"abstract_inverted_index":{"The":[0,63,78],"probability":[1,36,87],"distribution":[2,37,88],"of":[3,14,18,76,89,98,103,114],"duration":[4,21,28,58,90],"is":[5,38,52,65],"a":[6,41,60],"critical":[7],"input":[8],"for":[9],"predicting":[10],"the":[11,19,34,73,85,94,100,112],"potential":[12],"impact":[13],"traffic":[15],"incidents.":[16],"Most":[17],"previous":[20],"prediction":[22],"models":[23],"are":[24],"discrete,":[25],"which":[26],"divide":[27],"into":[29],"several":[30],"intervals.":[31],"However,":[32],"sometimes":[33],"continuous":[35,42,86],"needed.":[39],"Therefore":[40],"model":[43,64],"based":[44],"on":[45],"latent":[46],"Gaussian":[47],"naive":[48],"Bayesian":[49],"(LGNB)":[50],"classifier":[51],"developed":[53],"in":[54],"this":[55],"paper,":[56],"assuming":[57],"fits":[59],"lognormal":[61],"distribution.":[62],"calibrated":[66],"and":[67,116],"tested":[68],"by":[69,106,111],"incident":[70],"records":[71],"from":[72],"Georgia":[74],"Department":[75],"Transportation.":[77],"results":[79],"show":[80],"that":[81],"LGNB":[82,107],"can":[83,108],"describe":[84],"well.":[91],"According":[92],"to":[93],"evidence":[95],"sensitivity":[96],"analysis":[97],"LGNB,":[99],"four":[101],"classes":[102],"incidents":[104],"classified":[105],"be":[109],"interpreted":[110],"level":[113],"severity":[115],"complexity.":[117]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
