{"id":"https://openalex.org/W7129101697","doi":"https://doi.org/10.1109/access.2026.3665185","title":"An Adaptive PCA-RF-WKNN Algorithm for High-Dimensional Semiconductor Defect Classification","display_name":"An Adaptive PCA-RF-WKNN Algorithm for High-Dimensional Semiconductor Defect Classification","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7129101697","doi":"https://doi.org/10.1109/access.2026.3665185"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3665185","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3665185","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3665185","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043094475","display_name":"Gongli Li","orcid":"https://orcid.org/0000-0003-0864-4858"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Gongli Li","raw_affiliation_strings":["School of Mechanical and Mechatronic Engineering, University of Technology Sydney, Ultimo, NSW, Australia"],"raw_orcid":"https://orcid.org/0009-0000-8739-9744","affiliations":[{"raw_affiliation_string":"School of Mechanical and Mechatronic Engineering, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126080530","display_name":"Yidie Luo","orcid":null},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yidie Luo","raw_affiliation_strings":["School of Mechanical and Mechatronic Engineering, University of Technology Sydney, Ultimo, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical and Mechatronic Engineering, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100693527","display_name":"Zhen Luo","orcid":"https://orcid.org/0009-0007-7831-9475"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zhen Luo","raw_affiliation_strings":["School of Mechanical and Mechatronic Engineering, University of Technology Sydney, Ultimo, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical and Mechatronic Engineering, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126095159","display_name":"Nick S. Bennet","orcid":null},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Nick S. Bennett","raw_affiliation_strings":["School of Mechanical and Mechatronic Engineering, University of Technology Sydney, Ultimo, NSW, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mechanical and Mechatronic Engineering, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126141157","display_name":"Mohammad S.Islam","orcid":null},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Mohammad S. Islam","raw_affiliation_strings":["School of Mechanical and Mechatronic Engineering, University of Technology Sydney, Ultimo, NSW, Australia"],"raw_orcid":"https://orcid.org/0000-0001-6264-3886","affiliations":[{"raw_affiliation_string":"School of Mechanical and Mechatronic Engineering, University of Technology Sydney, Ultimo, NSW, Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":{"value":2075,"currency":"USD","value_usd":2075},"apc_paid":{"value":2075,"currency":"USD","value_usd":2075},"fwci":5.6289,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.92793081,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"14","issue":null,"first_page":"34252","last_page":"34270"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.4729999899864197,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.4729999899864197,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.10980000346899033,"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/T11032","display_name":"VLSI and Analog Circuit Testing","score":0.030500000342726707,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"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/benchmark","display_name":"Benchmark (surveying)","score":0.7408999800682068},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.6453999876976013},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.5875999927520752},{"id":"https://openalex.org/keywords/wilcoxon-signed-rank-test","display_name":"Wilcoxon signed-rank test","score":0.5436000227928162},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.49869999289512634},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49799999594688416},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.475600004196167},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.47360000014305115}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7408999800682068},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6779000163078308},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.6453999876976013},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.5875999927520752},{"id":"https://openalex.org/C206041023","wikidata":"https://www.wikidata.org/wiki/Q1751970","display_name":"Wilcoxon signed-rank test","level":3,"score":0.5436000227928162},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5205000042915344},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.49869999289512634},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49799999594688416},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.475600004196167},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.47360000014305115},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.47110000252723694},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.46209999918937683},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4577000141143799},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44519999623298645},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.42879998683929443},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.3650999963283539},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.3619000017642975},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3370000123977661},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.31439998745918274},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2989000082015991},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.2621000111103058},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.2508000135421753}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3665185","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3665185","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:1a40ccb38b0e43d7babef1c9fd20d203","is_oa":true,"landing_page_url":"https://doaj.org/article/1a40ccb38b0e43d7babef1c9fd20d203","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 34252-34270 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3665185","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3665185","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4029539227485657,"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15"}],"awards":[{"id":"https://openalex.org/G4694861915","display_name":null,"funder_award_id":"202308200008","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"}],"funders":[{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W46832713","https://openalex.org/W1500895378","https://openalex.org/W1520812622","https://openalex.org/W1827261456","https://openalex.org/W1857789879","https://openalex.org/W1875061881","https://openalex.org/W1966701961","https://openalex.org/W1982772336","https://openalex.org/W2046468425","https://openalex.org/W2080931119","https://openalex.org/W2092669780","https://openalex.org/W2096733369","https://openalex.org/W2109363337","https://openalex.org/W2109628770","https://openalex.org/W2118123209","https://openalex.org/W2124563089","https://openalex.org/W2128040385","https://openalex.org/W2131987814","https://openalex.org/W2136132422","https://openalex.org/W2138451337","https://openalex.org/W2147717514","https://openalex.org/W2149684740","https://openalex.org/W2154053567","https://openalex.org/W2160643014","https://openalex.org/W2165558283","https://openalex.org/W2169495281","https://openalex.org/W2221243399","https://openalex.org/W2294798173","https://openalex.org/W2310372181","https://openalex.org/W2314669497","https://openalex.org/W2736435690","https://openalex.org/W2759390927","https://openalex.org/W2766450228","https://openalex.org/W2885402671","https://openalex.org/W2914655456","https://openalex.org/W2964300371","https://openalex.org/W2991486297","https://openalex.org/W2998026623","https://openalex.org/W3000707849","https://openalex.org/W3007136938","https://openalex.org/W3013070828","https://openalex.org/W3029425897","https://openalex.org/W3043942921","https://openalex.org/W3148981562","https://openalex.org/W3171588328","https://openalex.org/W3180610907","https://openalex.org/W4200535792","https://openalex.org/W4212883601","https://openalex.org/W4238805501","https://openalex.org/W4244777963","https://openalex.org/W4249992252","https://openalex.org/W4254687493","https://openalex.org/W4313509086","https://openalex.org/W4327519303","https://openalex.org/W4385000969","https://openalex.org/W4385485259","https://openalex.org/W4399715029","https://openalex.org/W4400762160","https://openalex.org/W4401495975","https://openalex.org/W4402391155","https://openalex.org/W4409390715","https://openalex.org/W4411044961","https://openalex.org/W4412747847"],"related_works":[],"abstract_inverted_index":{"The":[0,67,85,129,145,155,178,207],"K-Nearest":[1],"Neighbors":[2],"algorithm":[3,86],"is":[4,137],"a":[5,238],"widely":[6],"used":[7],"machine":[8],"learning":[9],"technique":[10],"for":[11,181,201,205,241],"classification":[12,104,191],"and":[13,21,31,53,78,116,126,174,203,224,236],"regression":[14],"tasks":[15],"due":[16],"to":[17,37,58,199],"its":[18],"simplicity,":[19],"interpretability,":[20],"effectiveness.":[22],"However,":[23],"KNN":[24,63,176,232],"suffers":[25],"from":[26],"the":[27,60,74,89,133,140,152,159,164,186,211,227],"curse":[28],"of":[29,62,76,92,132,168,196],"dimensionality":[30],"increased":[32],"computational":[33,70],"complexity":[34,71],"when":[35],"applied":[36],"high-dimensional":[38,65,103,242],"datasets.":[39],"This":[40],"paper":[41],"proposes":[42],"an":[43,194],"adaptive":[44],"algorithm,":[45],"termed":[46],"PCA-RF-WKNN.":[47],"It":[48],"combines":[49],"Principal":[50],"Component":[51],"Analysis":[52],"Random":[54],"Forest-based":[55],"feature":[56],"weighting":[57],"address":[59],"challenges":[61],"in":[64],"spaces.":[66],"method":[68],"reduces":[69],"by":[72],"lowering":[73],"number":[75,91],"dimensions":[77],"improves":[79],"distance":[80],"calculations":[81],"through":[82],"weighted":[83],"features.":[84],"dynamically":[87],"selects":[88],"optimal":[90],"neighbors(k)and":[93],"PCA":[94],"components(m)based":[95],"on":[96,151],"cross-validation.":[97],"A":[98],"comprehensive":[99],"evaluation":[100,148],"across":[101,214],"four":[102],"benchmark":[105,212],"datasets\u2014including":[106],"SECOM":[107,153],"semiconductor":[108],"manufacturing,":[109],"LSVT":[110],"Voice":[111],"Rehabilitation,":[112],"Steel":[113],"Plates":[114],"Faults,":[115],"Leukemia":[117],"Gene":[118],"Expression\u2014shows":[119],"that":[120,158],"PCA-RF-WKNN":[121,161,182,208],"consistently":[122],"outperforms":[123,210],"both":[124,171],"PCA-KNN":[125,172,202],"standard":[127,175],"KNN.":[128,206],"statistical":[130],"significance":[131],"observed":[134],"performance":[135,217],"improvements":[136],"validated":[138],"using":[139],"paired":[141],"Wilcoxon":[142],"signed-rank":[143],"test.":[144],"primary":[146],"experimental":[147],"was":[149],"conducted":[150],"dataset.":[154],"results":[156],"demonstrate":[157],"proposed":[160,228],"model":[162,209],"achieves":[163],"highest":[165],"testing":[166],"accuracy":[167],"0.962,":[169],"outperforming":[170],"(0.923)":[173],"(0.863).":[177],"ROC":[179],"curve":[180],"rises":[183],"steeply":[184],"toward":[185],"top-left":[187],"corner,":[188],"indicating":[189],"strong":[190],"capability,":[192],"with":[193],"AUC":[195],"0.900,":[197],"compared":[198],"0.816":[200],"0.701":[204],"models":[213],"all":[215],"key":[216],"metrics,":[218],"including":[219],"accuracy,":[220],"precision,":[221],"sensitivity,":[222],"F1-score,":[223],"ROC-AUC.":[225],"Overall,":[226],"approach":[229],"significantly":[230],"enhances":[231],"performance,":[233],"surpasses":[234],"PCA-KNN,":[235],"provides":[237],"promising":[239],"solution":[240],"data":[243],"problems.":[244]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2026-02-17T00:00:00"}
