{"id":"https://openalex.org/W4313459286","doi":"https://doi.org/10.1109/iccr56254.2022.9995895","title":"Retracted: Detection of forest fire using support vector machine in comparison with random forest to measure accuracy, precision and recall","display_name":"Retracted: Detection of forest fire using support vector machine in comparison with random forest to measure accuracy, precision and recall","publication_year":2022,"publication_date":"2022-10-06","ids":{"openalex":"https://openalex.org/W4313459286","doi":"https://doi.org/10.1109/iccr56254.2022.9995895"},"language":"en","primary_location":{"id":"doi:10.1109/iccr56254.2022.9995895","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccr56254.2022.9995895","pdf_url":null,"source":{"id":"https://openalex.org/S4363608155","display_name":"2022 International Conference on Cyber Resilience (ICCR)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Cyber Resilience (ICCR)","raw_type":"proceedings-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/A5058676153","display_name":"Inturi Susmitha","orcid":null},"institutions":[{"id":"https://openalex.org/I85461943","display_name":"Saveetha University","ror":"https://ror.org/0034me914","country_code":"IN","type":"education","lineage":["https://openalex.org/I85461943"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Inturi Susmitha","raw_affiliation_strings":["Saveetha University,Department of computer science and Engineering,Chennai,India","Department of computer science and Engineering, Saveetha University, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Saveetha University,Department of computer science and Engineering,Chennai,India","institution_ids":["https://openalex.org/I85461943"]},{"raw_affiliation_string":"Department of computer science and Engineering, Saveetha University, Chennai, India","institution_ids":["https://openalex.org/I85461943"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019850270","display_name":"Roseline J Femila","orcid":null},"institutions":[{"id":"https://openalex.org/I85461943","display_name":"Saveetha University","ror":"https://ror.org/0034me914","country_code":"IN","type":"education","lineage":["https://openalex.org/I85461943"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Roseline J Femila","raw_affiliation_strings":["Saveetha University,Department of computer science and Engineering,Chennai,India","Department of computer science and Engineering, Saveetha University, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Saveetha University,Department of computer science and Engineering,Chennai,India","institution_ids":["https://openalex.org/I85461943"]},{"raw_affiliation_string":"Department of computer science and Engineering, Saveetha University, Chennai, India","institution_ids":["https://openalex.org/I85461943"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020860405","display_name":"Vinay Sivasamy","orcid":null},"institutions":[{"id":"https://openalex.org/I85461943","display_name":"Saveetha University","ror":"https://ror.org/0034me914","country_code":"IN","type":"education","lineage":["https://openalex.org/I85461943"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vinay Sivasamy","raw_affiliation_strings":["Saveetha University,Department of computer science and Engineering,Chennai,India","Department of computer science and Engineering, Saveetha University, Chennai, India"],"affiliations":[{"raw_affiliation_string":"Saveetha University,Department of computer science and Engineering,Chennai,India","institution_ids":["https://openalex.org/I85461943"]},{"raw_affiliation_string":"Department of computer science and Engineering, Saveetha University, Chennai, India","institution_ids":["https://openalex.org/I85461943"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5058676153"],"corresponding_institution_ids":["https://openalex.org/I85461943"],"apc_list":null,"apc_paid":null,"fwci":0.564,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.89531406,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"06"},"is_retracted":true,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.9998000264167786,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9998000264167786,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9944000244140625,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10555","display_name":"Fire effects on ecosystems","score":0.9661999940872192,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.9307807683944702},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.8838536143302917},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5807535648345947},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.5662122368812561},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.44634366035461426},{"id":"https://openalex.org/keywords/recall","display_name":"Recall","score":0.42559659481048584},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35923486948013306},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34160375595092773},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3269948959350586}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.9307807683944702},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8838536143302917},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5807535648345947},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.5662122368812561},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44634366035461426},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.42559659481048584},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35923486948013306},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34160375595092773},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3269948959350586},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/iccr56254.2022.9995895","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccr56254.2022.9995895","pdf_url":null,"source":{"id":"https://openalex.org/S4363608155","display_name":"2022 International Conference on Cyber Resilience (ICCR)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 International Conference on Cyber Resilience (ICCR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6800000071525574,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1996518383","https://openalex.org/W2023493817","https://openalex.org/W2091125363","https://openalex.org/W2162303042","https://openalex.org/W2259037997","https://openalex.org/W2482136251","https://openalex.org/W2522163200","https://openalex.org/W2617142921","https://openalex.org/W2625116763","https://openalex.org/W2768959465","https://openalex.org/W2807719021","https://openalex.org/W2811209989","https://openalex.org/W2915876222","https://openalex.org/W2921214912","https://openalex.org/W2943468081","https://openalex.org/W2952038015","https://openalex.org/W2953144857","https://openalex.org/W2960646647","https://openalex.org/W2964673972","https://openalex.org/W2966457663","https://openalex.org/W2969273852","https://openalex.org/W2972865390","https://openalex.org/W2997335567","https://openalex.org/W3003421198","https://openalex.org/W3004245667","https://openalex.org/W3005999426","https://openalex.org/W3010458811","https://openalex.org/W3014625307","https://openalex.org/W3022979107","https://openalex.org/W3024479384","https://openalex.org/W3027872128","https://openalex.org/W3029903276","https://openalex.org/W3038830664","https://openalex.org/W3040858448","https://openalex.org/W3102380346","https://openalex.org/W3114164619","https://openalex.org/W3124739300","https://openalex.org/W3134184177","https://openalex.org/W3141387993","https://openalex.org/W3205520011","https://openalex.org/W4237588971","https://openalex.org/W4281714334"],"related_works":["https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W4200112873","https://openalex.org/W2955796858","https://openalex.org/W4224941037","https://openalex.org/W2004826645","https://openalex.org/W3135818052","https://openalex.org/W2358294942","https://openalex.org/W4385192698","https://openalex.org/W4367460280"],"abstract_inverted_index":{"Machine":[0,33,100],"learning":[1],"techniques":[2],"are":[3,51,62,88],"widely":[4],"used":[5],"in":[6,15,34,57,175],"forest":[7,174,178],"fire":[8,179],"detection":[9,41,176],"due":[10],"to":[11,25,90],"its":[12],"accurate":[13],"results":[14],"detection.":[16],"The":[17,149],"main":[18],"objective":[19],"of":[20,29,42,48,94,109,177],"this":[21,159],"proposed":[22],"work":[23],"is":[24,124,139,153,162],"evaluate":[26,91],"the":[27,54,68,92,95,121,165,172,181],"performance":[28,93],"Novel":[30,96,102],"Support":[31,98,104],"Vector":[32,99],"comparison":[35],"with":[36],"Random":[37,113,131,146,173],"Forest":[38,43,114,132,147],"algorithm":[39,115,123,138,167],"for":[40,67,77,120,130,136,145,180],"fire.":[44],"A":[45],"total":[46],"no":[47],"1599":[49],"samples":[50,61],"collected":[52],"from":[53],"dataset":[55,70,79,182],"available":[56],"UCI":[58],"Repository.":[59],"These":[60],"divided":[63],"into":[64],"70":[65],"%":[66,76,111,126,129,141,144],"training":[69],"(n":[71,80],"=":[72,81],"1119)":[73],"and":[74,85,127,142],"30":[75],"testing":[78],"480).":[82],"Accuracy,":[83],"Recall":[84,134],"Precision":[86,118],"values":[87],"determined":[89],"Linear":[97,103],"algorithm.":[101,133,148],"vector":[105],"machine":[106],"achieved":[107,116,152],"accuracy":[108],"96":[110],"whereas":[112],"78.50%.":[117],"obtained":[119,135],"SVM":[122,137,166],"94.04":[125],"73.05":[128],"94.13":[140],"78.52":[143],"significant":[150],"value":[151],"0.025":[154],"(p":[155],"\u00a1":[156],"0.05).":[157],"In":[158],"study,":[160],"it":[161],"observed":[163],"that":[164],"performed":[168],"significantly":[169],"better":[170],"than":[171],"examined.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2023-01-06T00:00:00"}
