{"id":"https://openalex.org/W4413204635","doi":"https://doi.org/10.1109/icetea64585.2025.11100107","title":"A Comparison of Machine Learning Models for the Quality of Red Wine","display_name":"A Comparison of Machine Learning Models for the Quality of Red Wine","publication_year":2025,"publication_date":"2025-06-05","ids":{"openalex":"https://openalex.org/W4413204635","doi":"https://doi.org/10.1109/icetea64585.2025.11100107"},"language":"en","primary_location":{"id":"doi:10.1109/icetea64585.2025.11100107","doi":"https://doi.org/10.1109/icetea64585.2025.11100107","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icetea64585.2025.11100107","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Emerging Technologies in Engineering Applications (ICETEA)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","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/A5090521293","display_name":"R. Karunamoorthi","orcid":"https://orcid.org/0009-0001-2141-6852","observed_orcids":["https://orcid.org/0009-0001-2141-6852"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karunamoorthi R","raw_affiliation_strings":["Kongu Engineering College,Department of CSE,Erode,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kongu Engineering College,Department of CSE,Erode,India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119302861","display_name":"K Rathidevi","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rathidevi K","raw_affiliation_strings":["Kongu Engineering College,Department of CSE,Erode,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kongu Engineering College,Department of CSE,Erode,India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119302862","display_name":"V Samuvel","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Samuvel V","raw_affiliation_strings":["Kongu Engineering College,Department of CSE,Erode,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kongu Engineering College,Department of CSE,Erode,India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059206927","display_name":"P Santhiya","orcid":"https://orcid.org/0000-0002-4818-3075","observed_orcids":["https://orcid.org/0000-0002-4818-3075"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Santhiya P","raw_affiliation_strings":["Kongu Engineering College,Department of CSE,Erode,India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kongu Engineering College,Department of CSE,Erode,India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.4216,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.89829719,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.8223000168800354,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.8223000168800354,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.05900000035762787,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10640","display_name":"Spectroscopy and Chemometric Analyses","score":0.033799998462200165,"subfield":{"id":"https://openalex.org/subfields/1602","display_name":"Analytical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/red-wine-quality","display_name":"red wine quality","score":0.8949999809265137},{"id":"https://openalex.org/keywords/wine-quality-prediction","display_name":"wine quality prediction","score":0.9679999947547913},{"id":"https://openalex.org/keywords/physicochemical-properties","display_name":"physicochemical properties","score":0.8989999890327454},{"id":"https://openalex.org/keywords/alcohol-content","display_name":"alcohol content","score":0.7239999771118164},{"id":"https://openalex.org/keywords/ph","display_name":"pH","score":0.9440000057220459},{"id":"https://openalex.org/keywords/acidity","display_name":"acidity","score":0.9539999961853027},{"id":"https://openalex.org/keywords/sulfur-dioxide","display_name":"sulfur dioxide","score":0.9959999918937683},{"id":"https://openalex.org/keywords/random-forest","display_name":"random forest","score":0.7670000195503235},{"id":"https://openalex.org/keywords/xgboost","display_name":"XGBoost","score":0.996999979019165},{"id":"https://openalex.org/keywords/catboost","display_name":"CatBoost","score":0.9449999928474426},{"id":"https://openalex.org/keywords/recursive-feature-elimination","display_name":"recursive feature elimination","score":0.8420000076293945},{"id":"https://openalex.org/keywords/feature-selection","display_name":"feature selection","score":0.9169999957084656},{"id":"https://openalex.org/keywords/wine-quality-control","display_name":"wine quality control","score":0.7519999742507935}],"concepts":[{"id":"https://openalex.org/C55952523","wikidata":"https://www.wikidata.org/wiki/Q3014419","display_name":"Wine","level":2,"score":0.8016185760498047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.655519962310791},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.633194088935852},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4441484808921814},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37806436419487},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0826522707939148},{"id":"https://openalex.org/C31903555","wikidata":"https://www.wikidata.org/wiki/Q1637030","display_name":"Food science","level":1,"score":0.06919977068901062},{"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:10.1109/icetea64585.2025.11100107","doi":"https://doi.org/10.1109/icetea64585.2025.11100107","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icetea64585.2025.11100107","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Conference on Emerging Technologies in Engineering Applications (ICETEA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"score":0.6000000238418579,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W2085254899","https://openalex.org/W2103459159","https://openalex.org/W2119505029","https://openalex.org/W2467694619","https://openalex.org/W2765832510","https://openalex.org/W3023295853","https://openalex.org/W3041981321","https://openalex.org/W3044108481","https://openalex.org/W4210666814","https://openalex.org/W4225884783"],"related_works":["https://openalex.org/W2961085424","https://openalex.org/W4306674287","https://openalex.org/W4387369504","https://openalex.org/W4394896187","https://openalex.org/W3170094116","https://openalex.org/W4386462264","https://openalex.org/W3107602296","https://openalex.org/W4364306694","https://openalex.org/W4312192474","https://openalex.org/W4283697347"],"abstract_inverted_index":{"The":[0,86],"objective":[1],"of":[2,10,23,34,83,88,151],"this":[3],"study":[4],"is":[5],"to":[6,19,74,79,105,117],"enhance":[7],"the":[8,21,32,49,81,84,89,132,138,149,152],"process":[9],"wine":[11,25,128],"quality":[12,22,124,150],"assessment":[13],"by":[14,130],"developing":[15],"a":[16,35],"machinelearning":[17],"model":[18,90],"predict":[20],"red":[24],"based":[26],"on":[27],"its":[28],"physicochemical":[29],"properties.":[30],"With":[31],"use":[33],"dataset":[36],"that":[37],"includes":[38],"characteristics":[39],"like":[40,97,107],"alcohol":[41],"content,":[42],"pH,":[43],"acidity,":[44],"and":[45,60,66,100,111,122,144],"sulfur":[46],"dioxide":[47],"levels,":[48],"project":[50],"uses":[51],"sophisticated":[52],"classification":[53],"algorithms":[54],"including":[55],"Random":[56],"Forest,":[57],"XG":[58],"Boost,":[59],"Cat":[61],"Boost.":[62],"Grid":[63],"Search":[64],"CV":[65],"Recursive":[67],"Feature":[68],"Elimination":[69],"(RFE)":[70],"will":[71,91,136],"be":[72,92],"applied":[73],"feature":[75],"selection":[76],"in":[77,103,148],"order":[78],"improve":[80],"performance":[82],"model.":[85],"effectiveness":[87],"evaluated":[93],"using":[94],"visual":[95],"aids":[96],"confusion":[98],"matrices":[99],"ROC":[101],"curves":[102],"addition":[104],"metrics":[106],"accuracy,":[108],"precision,":[109],"recall,":[110],"F1":[112],"score.":[113],"This":[114,135],"strategy":[115],"seeks":[116],"provide":[118],"an":[119],"accurate,":[120],"economical,":[121],"effective":[123],"control":[125],"solution":[126],"for":[127,140],"production":[129],"automating":[131],"prediction":[133],"process.":[134],"lessen":[137],"need":[139],"conventional":[141],"testing":[142],"techniques":[143],"guarantee":[145],"higher":[146],"consistency":[147],"final":[153],"product.":[154]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-10-09T09:14:12.587421","created_date":"2025-10-10T00:00:00"}