{"id":"https://openalex.org/W1936747996","doi":"https://doi.org/10.3233/his-2011-0132","title":"Feature and algorithm selection with Hybrid Intelligent Techniques","display_name":"Feature and algorithm selection with Hybrid Intelligent Techniques","publication_year":2011,"publication_date":"2011-06-17","ids":{"openalex":"https://openalex.org/W1936747996","doi":"https://doi.org/10.3233/his-2011-0132","mag":"1936747996"},"language":"en","primary_location":{"id":"doi:10.3233/his-2011-0132","is_oa":true,"landing_page_url":"https://doi.org/10.3233/his-2011-0132","pdf_url":"https://content.iospress.com:443/download/international-journal-of-hybrid-intelligent-systems/his00132?id=international-journal-of-hybrid-intelligent-systems%2Fhis00132","source":{"id":"https://openalex.org/S50927259","display_name":"International Journal of Hybrid Intelligent Systems","issn_l":"1448-5869","issn":["1448-5869","1875-8819"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Hybrid Intelligent Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://content.iospress.com:443/download/international-journal-of-hybrid-intelligent-systems/his00132?id=international-journal-of-hybrid-intelligent-systems%2Fhis00132","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025550530","display_name":"Teresa B. Ludermir","orcid":"https://orcid.org/0000-0002-8980-6742"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":true,"raw_author_name":"Teresa B. Ludermir","raw_affiliation_strings":["Federal University of Pernambuco, Recife, Brazil","(Correspd. E-mail: tbl@cin.ufpe.br) Federal University of Pernambuco, Recife, Brazil#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Pernambuco, Recife, Brazil","institution_ids":["https://openalex.org/I25112270"]},{"raw_affiliation_string":"(Correspd. E-mail: tbl@cin.ufpe.br) Federal University of Pernambuco, Recife, Brazil#TAB#","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083998049","display_name":"Ricardo B. C. Prud\u00eancio","orcid":"https://orcid.org/0000-0001-7084-1233"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Ricardo B.C. Prud\u00eancio","raw_affiliation_strings":["Federal University of Pernambuco, Recife, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Pernambuco, Recife, Brazil","institution_ids":["https://openalex.org/I25112270"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086345001","display_name":"Cleber Zanchettin","orcid":"https://orcid.org/0000-0001-6421-9747"},"institutions":[{"id":"https://openalex.org/I25112270","display_name":"Universidade Federal de Pernambuco","ror":"https://ror.org/047908t24","country_code":"BR","type":"education","lineage":["https://openalex.org/I25112270"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Cleber Zanchettin","raw_affiliation_strings":["Federal University of Pernambuco, Recife, Brazil"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Federal University of Pernambuco, Recife, Brazil","institution_ids":["https://openalex.org/I25112270"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5025550530"],"corresponding_institution_ids":["https://openalex.org/I25112270"],"apc_list":null,"apc_paid":null,"fwci":1.2941,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.83082308,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"8","issue":"3","first_page":"115","last_page":"116"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.8597000241279602,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.8597000241279602,"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.7807000279426575,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.7584999799728394,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7999244928359985},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.6330620646476746},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6258106827735901},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6054990887641907},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.5549589991569519},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5311169624328613},{"id":"https://openalex.org/keywords/meta-learning","display_name":"Meta learning (computer science)","score":0.5201330780982971},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.47619903087615967},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.47194093465805054},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4641268253326416},{"id":"https://openalex.org/keywords/hybrid-algorithm","display_name":"Hybrid algorithm (constraint satisfaction)","score":0.43915534019470215},{"id":"https://openalex.org/keywords/travelling-salesman-problem","display_name":"Travelling salesman problem","score":0.4387006461620331},{"id":"https://openalex.org/keywords/online-machine-learning","display_name":"Online machine learning","score":0.4101022779941559},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.24314051866531372}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7999244928359985},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.6330620646476746},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6258106827735901},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6054990887641907},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.5549589991569519},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5311169624328613},{"id":"https://openalex.org/C2781002164","wikidata":"https://www.wikidata.org/wiki/Q6822311","display_name":"Meta learning (computer science)","level":3,"score":0.5201330780982971},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47619903087615967},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.47194093465805054},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4641268253326416},{"id":"https://openalex.org/C62469222","wikidata":"https://www.wikidata.org/wiki/Q17092103","display_name":"Hybrid algorithm (constraint satisfaction)","level":5,"score":0.43915534019470215},{"id":"https://openalex.org/C175859090","wikidata":"https://www.wikidata.org/wiki/Q322212","display_name":"Travelling salesman problem","level":2,"score":0.4387006461620331},{"id":"https://openalex.org/C115903097","wikidata":"https://www.wikidata.org/wiki/Q7094097","display_name":"Online machine learning","level":3,"score":0.4101022779941559},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.24314051866531372},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C176783269","wikidata":"https://www.wikidata.org/wiki/Q5164378","display_name":"Constraint logic programming","level":4,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.0},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.0},{"id":"https://openalex.org/C44616089","wikidata":"https://www.wikidata.org/wiki/Q30158686","display_name":"Constraint satisfaction","level":3,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/his-2011-0132","is_oa":true,"landing_page_url":"https://doi.org/10.3233/his-2011-0132","pdf_url":"https://content.iospress.com:443/download/international-journal-of-hybrid-intelligent-systems/his00132?id=international-journal-of-hybrid-intelligent-systems%2Fhis00132","source":{"id":"https://openalex.org/S50927259","display_name":"International Journal of Hybrid Intelligent Systems","issn_l":"1448-5869","issn":["1448-5869","1875-8819"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Hybrid Intelligent Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.3233/his-2011-0132","is_oa":true,"landing_page_url":"https://doi.org/10.3233/his-2011-0132","pdf_url":"https://content.iospress.com:443/download/international-journal-of-hybrid-intelligent-systems/his00132?id=international-journal-of-hybrid-intelligent-systems%2Fhis00132","source":{"id":"https://openalex.org/S50927259","display_name":"International Journal of Hybrid Intelligent Systems","issn_l":"1448-5869","issn":["1448-5869","1875-8819"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Hybrid Intelligent Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W1936747996.pdf","grobid_xml":"https://content.openalex.org/works/W1936747996.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3112308976","https://openalex.org/W4210507159","https://openalex.org/W2091347716","https://openalex.org/W3200361725","https://openalex.org/W2137825550","https://openalex.org/W4319309271","https://openalex.org/W2749328462","https://openalex.org/W4376652622","https://openalex.org/W2980742310","https://openalex.org/W2408703238"],"abstract_inverted_index":{"There":[0],"are":[1,13,47,100],"many":[2,88],"ad":[3],"hoc":[4],"feature":[5,27],"and":[6,28,72,90,147],"algorithm":[7,29,73,138,156,175,210],"selection":[8,30,74,157,204],"techniques,":[9],"but":[10],"there":[11],"also":[12],"more":[14],"methodical":[15],"approaches.":[16,164],"From":[17],"a":[18,42,61,142,148,199,212],"theoretical":[19],"perspective,":[20],"it":[21],"can":[22,159],"be":[23,131,160],"shown":[24],"that":[25],"optimal":[26,69],"require":[31],"an":[32,68],"exhaustive":[33],"search":[34,56],"of":[35,39,45,64,67,79,96,98,151,174,181,205,215,225],"all":[36],"possible":[37],"subsets":[38],"features/algorithms.":[40],"If":[41],"large":[43],"number":[44],"features/algorithms":[46],"available,":[48],"this":[49,182],"is":[50,57],"impractical.":[51],"In":[52,121,177],"machine":[53],"learning,":[54],"the":[55,77,109,125,155,172,178,203,206,216,223,226],"often":[58],"done":[59],"for":[60,86,111,137,145,171,202,211],"satisfactory":[62],"set":[63],"features/algorithm":[65],"instead":[66],"set.":[70],"Feature":[71],"have":[75,168],"become":[76],"focus":[78],"some":[80],"research":[81],"in":[82,117],"hybrid":[83],"intelligent":[84,115],"systems,":[85],"which":[87],"algorithms":[89,129,189],"datasets,":[91],"with":[92],"tens":[93],"or":[94],"hundreds":[95],"thousands":[97],"variables,":[99],"available.":[101],"Hybrid":[102],"Intelligent":[103],"Systems":[104],"gather":[105],"researchers":[106],"who":[107],"see":[108],"need":[110,144],"synergy":[112],"between":[113],"various":[114],"techniques":[116],"solving":[118],"real":[119],"problems.":[120],"order":[122],"to":[123,133,141,190],"minimize":[124],"above":[126],"difficulty,":[127],"machinelearning":[128],"may":[130],"used":[132],"automatically":[134],"acquire":[135],"knowledge":[136],"selection,":[139],"leading":[140],"reduced":[143],"experts":[146],"potential":[149],"improvement":[150],"performance.":[152],"That":[153],"is,":[154],"problem":[158,173,194],"treated":[161],"via":[162],"meta-learning":[163,166,227],"Several":[165,220],"approaches":[167],"been":[169],"developed":[170],"selection.":[176],"first":[179],"article":[180],"special":[183],"issue,":[184],"Kanda":[185],"et":[186],"al.":[187],"select":[188],"solve":[191],"traveling":[192,217],"salesman":[193,218],"using":[195],"meta-learning.":[196],"Meta-learning":[197],"provides":[198],"suitable":[200],"technique":[201],"most":[207],"promising":[208],"optimization":[209],"specific":[213],"instance":[214],"problem.":[219],"experiments":[221],"illustrate":[222],"performance":[224],"based":[228],"approach":[229],"proposed.":[230]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-06-23T06:36:01.041984","created_date":"2025-10-10T00:00:00"}