{"id":"https://openalex.org/W2027720851","doi":"https://doi.org/10.2478/jaiscr-2014-0023","title":"Maximising Accuracy and Efficiency of Traffic Accident Prediction Combining Information Mining with Computational Intelligence Approaches and Decision Trees","display_name":"Maximising Accuracy and Efficiency of Traffic Accident Prediction Combining Information Mining with Computational Intelligence Approaches and Decision Trees","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2027720851","doi":"https://doi.org/10.2478/jaiscr-2014-0023","mag":"2027720851"},"language":"en","primary_location":{"id":"doi:10.2478/jaiscr-2014-0023","is_oa":true,"landing_page_url":"https://doi.org/10.2478/jaiscr-2014-0023","pdf_url":"https://www.sciendo.com/pdf/10.2478/jaiscr-2014-0023","source":{"id":"https://openalex.org/S4210223945","display_name":"Journal of Artificial Intelligence and Soft Computing Research","issn_l":"2083-2567","issn":["2083-2567","2449-6499"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317241","host_organization_name":"Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology","host_organization_lineage":["https://openalex.org/P4310317241"],"host_organization_lineage_names":["Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Artificial Intelligence and Soft Computing Research","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.sciendo.com/pdf/10.2478/jaiscr-2014-0023","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042324616","display_name":"Tatiana Tambouratzis","orcid":"https://orcid.org/0000-0002-8666-1381"},"institutions":[{"id":"https://openalex.org/I154757721","display_name":"University of Piraeus","ror":"https://ror.org/02qs84g94","country_code":"GR","type":"education","lineage":["https://openalex.org/I154757721"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"Tatiana Tambouratzis","raw_affiliation_strings":["Department of Industrial Management & Technology, University of Piraeus, 107 Deligiorgi St, Piraeus 185 34, Greece","Department of Industrial Management and Technology, University of Piraeus, 107 Deligiorgi St., Piraeus 185 34, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Industrial Management & Technology, University of Piraeus, 107 Deligiorgi St, Piraeus 185 34, Greece","institution_ids":["https://openalex.org/I154757721"]},{"raw_affiliation_string":"Department of Industrial Management and Technology, University of Piraeus, 107 Deligiorgi St., Piraeus 185 34, Greece","institution_ids":["https://openalex.org/I154757721"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074713280","display_name":"Dora Souliou","orcid":null},"institutions":[{"id":"https://openalex.org/I174458059","display_name":"National Technical University of Athens","ror":"https://ror.org/03cx6bg69","country_code":"GR","type":"education","lineage":["https://openalex.org/I174458059"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Dora Souliou","raw_affiliation_strings":["School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou St, Zografou 15780, Greece"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou St, Zografou 15780, Greece","institution_ids":["https://openalex.org/I174458059"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043738228","display_name":"Miltiadis Chalikias","orcid":"https://orcid.org/0000-0003-1482-0926"},"institutions":[{"id":"https://openalex.org/I122380217","display_name":"Technological Educational Institute of Piraeus","ror":"https://ror.org/00ks0ea23","country_code":"GR","type":"education","lineage":["https://openalex.org/I122380217"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Miltiadis Chalikias","raw_affiliation_strings":["Department of Business Administration, Technological Educational Institution of Peiraius, 250 Thivon and Petrou Ralli Av., 122 44 Egaleo, Greece"],"affiliations":[{"raw_affiliation_string":"Department of Business Administration, Technological Educational Institution of Peiraius, 250 Thivon and Petrou Ralli Av., 122 44 Egaleo, Greece","institution_ids":["https://openalex.org/I122380217"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020514740","display_name":"Andreas Gregoriades","orcid":"https://orcid.org/0000-0002-7422-1514"},"institutions":[{"id":"https://openalex.org/I201118511","display_name":"European University Cyprus","ror":"https://ror.org/04xp48827","country_code":"CY","type":"education","lineage":["https://openalex.org/I201118511"]}],"countries":["CY"],"is_corresponding":false,"raw_author_name":"Andreas Gregoriades","raw_affiliation_strings":["Department of Computer Science & Engineering, European University Cyprus, Cyprus"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science & Engineering, European University Cyprus, Cyprus","institution_ids":["https://openalex.org/I201118511"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5042324616"],"corresponding_institution_ids":["https://openalex.org/I154757721"],"apc_list":null,"apc_paid":null,"fwci":4.3503,"has_fulltext":true,"cited_by_count":36,"citation_normalized_percentile":{"value":0.93205261,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"4","issue":"1","first_page":"31","last_page":"42"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10370","display_name":"Traffic and Road Safety","score":0.9995999932289124,"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":0.9995999932289124,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.998199999332428,"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/T10809","display_name":"Occupational Health and Safety Research","score":0.9643999934196472,"subfield":{"id":"https://openalex.org/subfields/3614","display_name":"Radiological and Ultrasound Technology"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.7120316028594971},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6528319120407104},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6337065100669861},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.5985303521156311},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.5746273994445801},{"id":"https://openalex.org/keywords/accident","display_name":"Accident (philosophy)","score":0.5709771513938904},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.5426800847053528},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5169988870620728},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5164101719856262},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5008349418640137},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4812324047088623},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4610087275505066},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.44335445761680603},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41222280263900757}],"concepts":[{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.7120316028594971},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6528319120407104},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6337065100669861},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.5985303521156311},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.5746273994445801},{"id":"https://openalex.org/C2780289543","wikidata":"https://www.wikidata.org/wiki/Q424630","display_name":"Accident (philosophy)","level":2,"score":0.5709771513938904},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5426800847053528},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5169988870620728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5164101719856262},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5008349418640137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4812324047088623},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4610087275505066},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.44335445761680603},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41222280263900757},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.2478/jaiscr-2014-0023","is_oa":true,"landing_page_url":"https://doi.org/10.2478/jaiscr-2014-0023","pdf_url":"https://www.sciendo.com/pdf/10.2478/jaiscr-2014-0023","source":{"id":"https://openalex.org/S4210223945","display_name":"Journal of Artificial Intelligence and Soft Computing Research","issn_l":"2083-2567","issn":["2083-2567","2449-6499"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317241","host_organization_name":"Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology","host_organization_lineage":["https://openalex.org/P4310317241"],"host_organization_lineage_names":["Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Artificial Intelligence and Soft Computing Research","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.2478/jaiscr-2014-0023","is_oa":true,"landing_page_url":"https://doi.org/10.2478/jaiscr-2014-0023","pdf_url":"https://www.sciendo.com/pdf/10.2478/jaiscr-2014-0023","source":{"id":"https://openalex.org/S4210223945","display_name":"Journal of Artificial Intelligence and Soft Computing Research","issn_l":"2083-2567","issn":["2083-2567","2449-6499"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317241","host_organization_name":"Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology","host_organization_lineage":["https://openalex.org/P4310317241"],"host_organization_lineage_names":["Polish Neural Network Society, the University of Social Sciences in Lodz & Czestochowa University of Technology"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Artificial Intelligence and Soft Computing Research","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7799999713897705,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2027720851.pdf","grobid_xml":"https://content.openalex.org/works/W2027720851.grobid-xml"},"referenced_works_count":73,"referenced_works":["https://openalex.org/W43260119","https://openalex.org/W187357405","https://openalex.org/W199384682","https://openalex.org/W581792737","https://openalex.org/W949293872","https://openalex.org/W1504480307","https://openalex.org/W1528905581","https://openalex.org/W1542422557","https://openalex.org/W1587362683","https://openalex.org/W1594031697","https://openalex.org/W1614435007","https://openalex.org/W1625504505","https://openalex.org/W1966398873","https://openalex.org/W1987193935","https://openalex.org/W1996206993","https://openalex.org/W2000513404","https://openalex.org/W2001619934","https://openalex.org/W2008909284","https://openalex.org/W2009395135","https://openalex.org/W2013845817","https://openalex.org/W2015020429","https://openalex.org/W2016927407","https://openalex.org/W2017337590","https://openalex.org/W2038175992","https://openalex.org/W2056208640","https://openalex.org/W2056981759","https://openalex.org/W2059386649","https://openalex.org/W2066509360","https://openalex.org/W2067885219","https://openalex.org/W2074191025","https://openalex.org/W2086927126","https://openalex.org/W2112419234","https://openalex.org/W2116045745","https://openalex.org/W2119755537","https://openalex.org/W2125055259","https://openalex.org/W2130949063","https://openalex.org/W2132735659","https://openalex.org/W2133097426","https://openalex.org/W2133487567","https://openalex.org/W2133990480","https://openalex.org/W2138745909","https://openalex.org/W2142635246","https://openalex.org/W2145680191","https://openalex.org/W2146200922","https://openalex.org/W2149706766","https://openalex.org/W2152938409","https://openalex.org/W2159110831","https://openalex.org/W2160172778","https://openalex.org/W2164855953","https://openalex.org/W2166103330","https://openalex.org/W2168175751","https://openalex.org/W2234902528","https://openalex.org/W2294798173","https://openalex.org/W2306760703","https://openalex.org/W2330820318","https://openalex.org/W2766736793","https://openalex.org/W2911964244","https://openalex.org/W2912565176","https://openalex.org/W2912934387","https://openalex.org/W3022903251","https://openalex.org/W3103913776","https://openalex.org/W3207342693","https://openalex.org/W4236137412","https://openalex.org/W4248841288","https://openalex.org/W4292471687","https://openalex.org/W4299511277","https://openalex.org/W4379510236","https://openalex.org/W6636859864","https://openalex.org/W6650842192","https://openalex.org/W6681987720","https://openalex.org/W6808111085","https://openalex.org/W6817491142","https://openalex.org/W6843735874"],"related_works":["https://openalex.org/W3193450055","https://openalex.org/W3165907317","https://openalex.org/W3210877509","https://openalex.org/W4293525103","https://openalex.org/W4308191010","https://openalex.org/W3150651898","https://openalex.org/W4318350883","https://openalex.org/W3168850895","https://openalex.org/W4362588981","https://openalex.org/W4362564095"],"abstract_inverted_index":{"Abstract":[0],"The":[1,56],"development":[2],"of":[3,13,26,31,53,66,69,92,96,103,131,143,147,152,155,159],"universal":[4],"methodologies":[5],"for":[6,43],"the":[7,28,44,51,64,70,93,100,104,116,153,156],"accurate,":[8],"efficient,":[9],"and":[10,17,35,90,127,139,145,161],"timely":[11],"prediction":[12,39,75,122,138],"traffic":[14],"accident":[15,37,46,71,120,148,171],"location":[16],"severity":[18,38,121],"constitutes":[19],"a":[20,140,167],"crucial":[21],"endeavour.":[22],"In":[23],"this":[24],"piece":[25],"research,":[27],"best":[29],"combinations":[30,158],"salient":[32,101],"accident-related":[33],"parameters":[34,72,160],"accurate":[36],"models":[40,162],"are":[41],"determined":[42],"2005":[45],"dataset":[47,117],"brought":[48],"together":[49],"by":[50,82],"Republic":[52],"Cyprus":[54],"Police.":[55],"optimal":[57,157],"methodology":[58],"involves:":[59],"(a)":[60],"information":[61,102],"mining":[62],"in":[63,115],"form":[65],"feature":[67,83],"selection":[68,91],"that":[73,98],"maximise":[74],"accuracy":[76],"(implemented":[77,85],"via":[78,86,123],"scatter":[79],"search),":[80],"followed":[81],"extraction":[84],"principal":[87],"component":[88],"analysis)":[89],"minimal":[94],"number":[95],"components":[97],"contain":[99],"original":[105],"parameters,":[106],"which":[107,132],"combined":[108],"bring":[109],"about":[110],"an":[111],"overall":[112],"74.42%":[113],"reduction":[114],"dimensionality;":[118],"(b)":[119],"probabilistic":[124],"neural":[125],"networks":[126],"random":[128],"forests,":[129],"both":[130],"independently":[133],"accomplish":[134],"over":[135],"96%":[136],"correct":[137],"balanced":[141],"proportion":[142],"under-":[144],"over-estimations":[146],"severity.":[149],"An":[150],"explanation":[151],"superiority":[154],"is":[163,166],"given,":[164],"as":[165],"comparison":[168],"with":[169],"existing":[170],"classification/prediction":[172],"approaches":[173]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":5}],"updated_date":"2025-12-10T02:45:41.426853","created_date":"2025-10-10T00:00:00"}
