{"id":"https://openalex.org/W1989499021","doi":"https://doi.org/10.4018/jdwm.2006070105","title":"Cluster-Based Input Selection for Transparent Fuzzy Modeling","display_name":"Cluster-Based Input Selection for Transparent Fuzzy Modeling","publication_year":2006,"publication_date":"2006-07-01","ids":{"openalex":"https://openalex.org/W1989499021","doi":"https://doi.org/10.4018/jdwm.2006070105","mag":"1989499021"},"language":"en","primary_location":{"id":"doi:10.4018/jdwm.2006070105","is_oa":false,"landing_page_url":"https://doi.org/10.4018/jdwm.2006070105","pdf_url":null,"source":{"id":"https://openalex.org/S53932126","display_name":"International Journal of Data Warehousing and Mining","issn_l":"1548-3924","issn":["1548-3924","1548-3932"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Warehousing and Mining","raw_type":"journal-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/A5013589322","display_name":"Can Yang","orcid":"https://orcid.org/0000-0001-7684-0987"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Can Yang","raw_affiliation_strings":["Zhejiang University, China","ZHEJIANG UNIVERSITY, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"ZHEJIANG UNIVERSITY, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100619149","display_name":"Jun Meng","orcid":"https://orcid.org/0000-0002-7633-3624"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Meng","raw_affiliation_strings":["Zhejiang University, China","ZHEJIANG UNIVERSITY, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"ZHEJIANG UNIVERSITY, China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"last","author":{"id":null,"display_name":"Shanan Zhu","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanan Zhu","raw_affiliation_strings":["Zhejiang University, China","ZHEJIANG UNIVERSITY, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, China","institution_ids":["https://openalex.org/I76130692"]},{"raw_affiliation_string":"ZHEJIANG UNIVERSITY, China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5013589322"],"corresponding_institution_ids":["https://openalex.org/I76130692"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.08438663,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":"3","first_page":"57","last_page":"75"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9800999760627747,"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/T10320","display_name":"Neural Networks and Applications","score":0.9800999760627747,"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":0.949400007724762,"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/T12135","display_name":"Fuzzy Systems and Optimization","score":0.9133999943733215,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8846070170402527},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.7551114559173584},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.6954002380371094},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6683946847915649},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5336739420890808},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.4831201732158661},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.45428797602653503},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42675361037254333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8846070170402527},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.7551114559173584},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.6954002380371094},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6683946847915649},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5336739420890808},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.4831201732158661},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.45428797602653503},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42675361037254333},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4018/jdwm.2006070105","is_oa":false,"landing_page_url":"https://doi.org/10.4018/jdwm.2006070105","pdf_url":null,"source":{"id":"https://openalex.org/S53932126","display_name":"International Journal of Data Warehousing and Mining","issn_l":"1548-3924","issn":["1548-3924","1548-3932"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Data Warehousing and Mining","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:igg:jdwm00:v:2:y:2006:i:3:p:57-75","is_oa":false,"landing_page_url":"https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jdwm.2006070105","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321012","display_name":"Technische Universiteit Delft","ror":"https://ror.org/02e2c7k09"},{"id":"https://openalex.org/F4320328099","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W2745001401","https://openalex.org/W4321353415","https://openalex.org/W2130974462","https://openalex.org/W972276598","https://openalex.org/W4246352526","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W2087343574","https://openalex.org/W4381571012"],"abstract_inverted_index":{"Input":[0,23],"selection":[1,24,37,47,147],"is":[2,48,59,67,84,104,121,153],"an":[3,13,55,145],"important":[4],"step":[5],"in":[6,30,94,172],"nonlinear":[7],"regression":[8],"modeling.":[9],"By":[10],"input":[11,36,45,63,99,146],"selection,":[12],"interpretable":[14],"model":[15,89,152],"can":[16,111],"be":[17,92,112],"built":[18,93],"with":[19,86,137,155],"less":[20],"computational":[21,102],"cost.":[22],"thus":[25],"has":[26],"drawn":[27],"great":[28],"attention":[29],"recent":[31],"years.":[32],"However,":[33],"most":[34],"available":[35],"methods":[38],"are":[39],"model-based.":[40],"In":[41,52],"this":[42,53],"case,":[43],"the":[44,62,101,118,132,167],"data":[46,109,142,173],"insensitive":[49],"to":[50,91],"changes.":[51],"paper,":[54],"effective":[56],"model-free":[57],"method":[58,66,83,120,134],"proposed":[60,82,119,133],"for":[61,96],"selection.":[64],"This":[65],"based":[68],"on":[69],"sensitivity":[70],"analysis":[71],"using":[72,124],"Minimum":[73],"Cluster":[74],"Volume":[75],"(MCV)":[76],"algorithm.":[77],"The":[78,115],"advantage":[79],"of":[80,108,117,158,163,169],"our":[81],"that":[85,131],"no":[87],"specific":[88],"needed":[90],"advance":[95],"checking":[97],"possible":[98],"combinations,":[100],"cost":[103],"reduced":[105],"and":[106,139,160],"changes":[107],"patterns":[110,170],"captured":[113],"automatically.":[114],"effectiveness":[116],"evaluated":[122],"by":[123],"three":[125],"well-known":[126],"benchmark":[127],"problems,":[128],"which":[129,165],"show":[130],"works":[135],"effectively":[136],"small":[138],"medium":[140],"sized":[141],"collections.":[143],"With":[144],"procedure,":[148],"a":[149],"concise":[150],"fuzzy":[151],"constructed":[154],"high":[156],"accuracy":[157],"prediction":[159],"better":[161],"interpretation":[162],"data,":[164],"serves":[166],"purpose":[168],"discovery":[171],"mining":[174],"well.":[175]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
