{"id":"https://openalex.org/W4410160038","doi":"https://doi.org/10.1007/s10791-025-09579-1","title":"Avoiding vehicle collisions in intersections using anomaly detection for the identification of chromatic index value in cubic graphs","display_name":"Avoiding vehicle collisions in intersections using anomaly detection for the identification of chromatic index value in cubic graphs","publication_year":2025,"publication_date":"2025-05-07","ids":{"openalex":"https://openalex.org/W4410160038","doi":"https://doi.org/10.1007/s10791-025-09579-1"},"language":"en","primary_location":{"id":"doi:10.1007/s10791-025-09579-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10791-025-09579-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10791-025-09579-1.pdf","source":{"id":"https://openalex.org/S5407036663","display_name":"Discover Computing","issn_l":"2948-2992","issn":["2948-2992"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://link.springer.com/content/pdf/10.1007/s10791-025-09579-1.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092104681","display_name":"Bianka Modrovi\u010dov\u00e1","orcid":null},"institutions":[{"id":"https://openalex.org/I59655833","display_name":"Matej Bel University","ror":"https://ror.org/016e5hy63","country_code":"SK","type":"education","lineage":["https://openalex.org/I59655833"]}],"countries":["SK"],"is_corresponding":false,"raw_author_name":"Bianka Modrovi\u010dov\u00e1","raw_affiliation_strings":["Department of Computer Science, Faculty of Natural Sciences, Matej Bel University, Tajovsk\u00e9ho 40, 97401, Bansk\u00e1 Bystrica, Slovakia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Faculty of Natural Sciences, Matej Bel University, Tajovsk\u00e9ho 40, 97401, Bansk\u00e1 Bystrica, Slovakia","institution_ids":["https://openalex.org/I59655833"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012027728","display_name":"Adam Dud\u00e1\u0161","orcid":"https://orcid.org/0000-0001-5517-9464"},"institutions":[{"id":"https://openalex.org/I59655833","display_name":"Matej Bel University","ror":"https://ror.org/016e5hy63","country_code":"SK","type":"education","lineage":["https://openalex.org/I59655833"]}],"countries":["SK"],"is_corresponding":true,"raw_author_name":"Adam Dud\u00e1\u0161","raw_affiliation_strings":["Department of Computer Science, Faculty of Natural Sciences, Matej Bel University, Tajovsk\u00e9ho 40, 97401, Bansk\u00e1 Bystrica, Slovakia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Faculty of Natural Sciences, Matej Bel University, Tajovsk\u00e9ho 40, 97401, Bansk\u00e1 Bystrica, Slovakia","institution_ids":["https://openalex.org/I59655833"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5012027728"],"corresponding_institution_ids":["https://openalex.org/I59655833"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04266261,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"28","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10400","display_name":"Network Security and Intrusion Detection","score":0.9876000285148621,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/index","display_name":"Index (typography)","score":0.6439653635025024},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.6290155649185181},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.6255613565444946},{"id":"https://openalex.org/keywords/chromatic-scale","display_name":"Chromatic scale","score":0.5482670068740845},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.5412487983703613},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5201583504676819},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.459812730550766},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.35788482427597046},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.30324655771255493},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.293368935585022},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.25410985946655273},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.16452261805534363},{"id":"https://openalex.org/keywords/quantum-mechanics","display_name":"Quantum mechanics","score":0.049091845750808716}],"concepts":[{"id":"https://openalex.org/C2777382242","wikidata":"https://www.wikidata.org/wiki/Q6017816","display_name":"Index (typography)","level":2,"score":0.6439653635025024},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.6290155649185181},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.6255613565444946},{"id":"https://openalex.org/C196956537","wikidata":"https://www.wikidata.org/wiki/Q202021","display_name":"Chromatic scale","level":2,"score":0.5482670068740845},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.5412487983703613},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5201583504676819},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.459812730550766},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.35788482427597046},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.30324655771255493},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.293368935585022},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.25410985946655273},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.16452261805534363},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.049091845750808716},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/s10791-025-09579-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10791-025-09579-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10791-025-09579-1.pdf","source":{"id":"https://openalex.org/S5407036663","display_name":"Discover Computing","issn_l":"2948-2992","issn":["2948-2992"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Computing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1007/s10791-025-09579-1","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s10791-025-09579-1","pdf_url":"https://link.springer.com/content/pdf/10.1007/s10791-025-09579-1.pdf","source":{"id":"https://openalex.org/S5407036663","display_name":"Discover Computing","issn_l":"2948-2992","issn":["2948-2992"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Computing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321779","display_name":"Ministerstvo \u0161kolstva, vedy, v\u00fdskumu a \u0161portu Slovenskej republiky","ror":"https://ror.org/044gwpv05"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4410160038.pdf","grobid_xml":"https://content.openalex.org/works/W4410160038.grobid-xml"},"referenced_works_count":35,"referenced_works":["https://openalex.org/W1828165169","https://openalex.org/W1958271191","https://openalex.org/W1978186735","https://openalex.org/W1995443851","https://openalex.org/W2068633285","https://openalex.org/W2089554624","https://openalex.org/W2785896737","https://openalex.org/W3039222472","https://openalex.org/W4232896595","https://openalex.org/W4287147252","https://openalex.org/W4296160236","https://openalex.org/W4303022245","https://openalex.org/W4315781029","https://openalex.org/W4379617065","https://openalex.org/W4384407578","https://openalex.org/W4386549315","https://openalex.org/W4389319314","https://openalex.org/W4390906336","https://openalex.org/W4391575455","https://openalex.org/W4392164154","https://openalex.org/W4400046281","https://openalex.org/W4400323786","https://openalex.org/W4401131884","https://openalex.org/W4401377092","https://openalex.org/W4401398485","https://openalex.org/W4402438214","https://openalex.org/W4403447209","https://openalex.org/W4404246980","https://openalex.org/W4405683823","https://openalex.org/W4405785352","https://openalex.org/W4405938470","https://openalex.org/W4406230663","https://openalex.org/W4406598481","https://openalex.org/W4406753857","https://openalex.org/W4408258230"],"related_works":["https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928","https://openalex.org/W2912112202","https://openalex.org/W4377864969","https://openalex.org/W3120251014"],"abstract_inverted_index":{"Abstract":[0],"In":[1],"traffic":[2,19,26],"management":[3],"and":[4,51,109,187,200,210,229,242,260,277],"urban":[5],"planning,":[6],"it":[7],"is":[8,27,71,156],"necessary":[9],"to":[10,29,73,163,170,196],"allocate":[11],"time":[12,69,273],"slots":[13,70],"for":[14,79,116,139],"the":[15,65,74,100,107,117,120,154,171,197,203,211,217,220,230,251,255],"free":[16],"flow":[17],"of":[18,40,56,67,76,83,93,102,111,119,123,127,153,190,205,207,213,223,234,254,275,283],"on":[20,31,42,106,216],"intersected":[21],"roads":[22,35],"so":[23],"that":[24],"no":[25],"allowed":[28],"course":[30],"any":[32],"two":[33],"adjacent":[34],"simultaneously,":[36],"therefore":[37],"avoiding":[38],"collisions":[39],"vehicles":[41],"said":[43],"intersections.":[44],"This":[45],"NP-complete":[46],"problem":[47,199],"can":[48],"be":[49],"modelled":[50],"solved":[52],"via":[53],"edge":[54,81,166],"coloring":[55,82],"a":[57,60,85,88,94,124,131,224],"graph":[58,86,165],"representing":[59],"selected":[61,125,198],"intersection":[62],"system,":[63,249],"where":[64,134],"number":[66,75],"needed":[68],"equal":[72],"colors":[77,137],"required":[78],"conflict-free":[80],"such":[84],"\u2212":[87,174,193],"property":[89],"called":[90],"chromatic":[91,121,284],"index":[92,122,285],"graph.":[95],"The":[96,150],"work":[97],"presented":[98],"in":[99,143,265],"scope":[101],"this":[103],"study":[104,155],"focuses":[105],"design":[108],"implementation":[110],"an":[112],"anomaly":[113,172,266],"detection":[114,173],"process":[115],"identification":[118],"subset":[126],"intersections":[128],"represented":[129],"by":[130],"cubic":[132],"graph,":[133],"conventionally":[135],"three":[136,188],"suffice":[138],"proper":[140],"coloring,":[141],"but":[142],"rare":[144],"(anomalous)":[145],"cases":[146],"four":[147],"are":[148,250],"needed.":[149],"main":[151],"objective":[152],"achieving":[157],"lower":[158],"computational":[159],"requirements":[160],"when":[161],"compared":[162],"standard":[164,280],"coloring.":[167],"Eight":[168],"approaches":[169,257,269],"isolation":[175],"forest,":[176,179,238],"one-class":[177],"random":[178,227,237],"multilayer":[180,239],"perceptron":[181,240],"network,":[182,241],"support":[183,243],"vector":[184,244],"machine,":[185],"encoder,":[186],"types":[189],"ensemble":[191,231],"models":[192],"were":[194],"applied":[195],"evaluated":[201],"from":[202],"point":[204],"view":[206],"decision-making":[208],"quality":[209],"duration":[212],"computation.":[214],"Based":[215],"reached":[218],"results,":[219],"simple":[221],"model":[222,232],"one":[225,235],"class":[226,236],"forest":[228],"consisting":[233],"machine":[245],"applying":[246],"AND":[247],"voting":[248],"most":[252],"fitting":[253],"considered":[256],"with":[258],"97%":[259],"99%":[261],"respective":[262],"recall":[263],"values":[264],"identification.":[267,286],"Both":[268],"also":[270],"reach":[271],"better":[272],"complexity":[274],"training":[276],"testing":[278],"than":[279],"edge-coloring":[281],"methods":[282]},"counts_by_year":[],"updated_date":"2026-06-13T06:13:01.061226","created_date":"2025-10-10T00:00:00"}
