{"id":"https://openalex.org/W2978873084","doi":"https://doi.org/10.1109/tfuzz.2019.2945535","title":"Robust Generalized Fuzzy Systems Training From High-Dimensional Time-Series Data Using Local Structure Preserving PLS","display_name":"Robust Generalized Fuzzy Systems Training From High-Dimensional Time-Series Data Using Local Structure Preserving PLS","publication_year":2019,"publication_date":"2019-10-04","ids":{"openalex":"https://openalex.org/W2978873084","doi":"https://doi.org/10.1109/tfuzz.2019.2945535","mag":"2978873084"},"language":"en","primary_location":{"id":"doi:10.1109/tfuzz.2019.2945535","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2019.2945535","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Fuzzy Systems","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/A5010578654","display_name":"Edwin Lughofer","orcid":"https://orcid.org/0000-0003-1560-5136"},"institutions":[{"id":"https://openalex.org/I121883995","display_name":"Johannes Kepler University of Linz","ror":"https://ror.org/052r2xn60","country_code":"AT","type":"education","lineage":["https://openalex.org/I121883995"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Edwin Lughofer","raw_affiliation_strings":["Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz, Linz, Austria"],"raw_orcid":"https://orcid.org/0000-0003-1560-5136","affiliations":[{"raw_affiliation_string":"Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz, Linz, Austria","institution_ids":["https://openalex.org/I121883995"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036971504","display_name":"Ramin Nikzad\u2010Langerodi","orcid":"https://orcid.org/0000-0003-3495-8949"},"institutions":[{"id":"https://openalex.org/I4210143077","display_name":"Research Center for Non Destructive Testing (Austria)","ror":"https://ror.org/05cndr128","country_code":"AT","type":"company","lineage":["https://openalex.org/I4210143077"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Ramin Nikzad-Langerodi","raw_affiliation_strings":["Research Center for Non-Destructive Testing GmbH, Linz, Austria"],"raw_orcid":"https://orcid.org/0000-0003-3495-8949","affiliations":[{"raw_affiliation_string":"Research Center for Non-Destructive Testing GmbH, Linz, Austria","institution_ids":["https://openalex.org/I4210143077"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.7059,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.78378269,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"28","issue":"11","first_page":"2930","last_page":"2943"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9984999895095825,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9984999895095825,"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/T10320","display_name":"Neural Networks and Applications","score":0.9962999820709229,"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":0.9894000291824341,"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/interpretability","display_name":"Interpretability","score":0.6080016493797302},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5527992844581604},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5458479523658752},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.44248756766319275},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.4391753077507019},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.4327510595321655},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.4171966016292572},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3887823224067688},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.36650580167770386},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34965765476226807},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3481292426586151},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.22349190711975098}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.6080016493797302},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5527992844581604},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5458479523658752},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.44248756766319275},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.4391753077507019},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.4327510595321655},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.4171966016292572},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3887823224067688},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.36650580167770386},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34965765476226807},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3481292426586151},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.22349190711975098}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tfuzz.2019.2945535","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tfuzz.2019.2945535","pdf_url":null,"source":{"id":"https://openalex.org/S134177497","display_name":"IEEE Transactions on Fuzzy Systems","issn_l":"1063-6706","issn":["1063-6706","1941-0034"],"is_oa":false,"is_in_doaj":false,"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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Fuzzy Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6495973529","display_name":null,"funder_award_id":"IWB2020","funder_id":"https://openalex.org/F4320335322","funder_display_name":"European Regional Development Fund"}],"funders":[{"id":"https://openalex.org/F4320335322","display_name":"European Regional Development Fund","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":83,"referenced_works":["https://openalex.org/W90286923","https://openalex.org/W322952782","https://openalex.org/W807996015","https://openalex.org/W1171650066","https://openalex.org/W1501364645","https://openalex.org/W1504199162","https://openalex.org/W1554944419","https://openalex.org/W1570834090","https://openalex.org/W1861537833","https://openalex.org/W1966089218","https://openalex.org/W1966654857","https://openalex.org/W1973058638","https://openalex.org/W1976967072","https://openalex.org/W1994616650","https://openalex.org/W1998726167","https://openalex.org/W2001112986","https://openalex.org/W2014158063","https://openalex.org/W2017806383","https://openalex.org/W2028549589","https://openalex.org/W2034637389","https://openalex.org/W2036984693","https://openalex.org/W2045544997","https://openalex.org/W2052873800","https://openalex.org/W2057974719","https://openalex.org/W2064675550","https://openalex.org/W2065299222","https://openalex.org/W2073503722","https://openalex.org/W2079325629","https://openalex.org/W2093768254","https://openalex.org/W2104128541","https://openalex.org/W2105109747","https://openalex.org/W2122825543","https://openalex.org/W2124531803","https://openalex.org/W2124776405","https://openalex.org/W2128161665","https://openalex.org/W2141639776","https://openalex.org/W2145487065","https://openalex.org/W2149846618","https://openalex.org/W2153196467","https://openalex.org/W2154872931","https://openalex.org/W2162635690","https://openalex.org/W2168029744","https://openalex.org/W2171033594","https://openalex.org/W2201004764","https://openalex.org/W2250086655","https://openalex.org/W2394226702","https://openalex.org/W2399774368","https://openalex.org/W2442657908","https://openalex.org/W2482635655","https://openalex.org/W2489292218","https://openalex.org/W2504751434","https://openalex.org/W2517372414","https://openalex.org/W2574867284","https://openalex.org/W2592023122","https://openalex.org/W2620633022","https://openalex.org/W2756444473","https://openalex.org/W2772159275","https://openalex.org/W2774334526","https://openalex.org/W2782299476","https://openalex.org/W2791000529","https://openalex.org/W2793135540","https://openalex.org/W2798056406","https://openalex.org/W2801451447","https://openalex.org/W2802161886","https://openalex.org/W2911964244","https://openalex.org/W2913399920","https://openalex.org/W2946345288","https://openalex.org/W2962072167","https://openalex.org/W2998216295","https://openalex.org/W3083750329","https://openalex.org/W3101749733","https://openalex.org/W4205699531","https://openalex.org/W4234672050","https://openalex.org/W4241025692","https://openalex.org/W4244017338","https://openalex.org/W4247067480","https://openalex.org/W4252684946","https://openalex.org/W4285719527","https://openalex.org/W4293223245","https://openalex.org/W6623034183","https://openalex.org/W6675374405","https://openalex.org/W6682644385","https://openalex.org/W7066667914"],"related_works":["https://openalex.org/W4396678544","https://openalex.org/W2945382830","https://openalex.org/W4224807364","https://openalex.org/W2596632494","https://openalex.org/W2535986621","https://openalex.org/W1980197432","https://openalex.org/W2382432689","https://openalex.org/W2000612978","https://openalex.org/W4388110928","https://openalex.org/W1483228865"],"abstract_inverted_index":{"Establishing":[0],"fuzzy":[1,70,84,90,151,168,243,330,389],"models":[2],"from":[3,145],"time-series":[4],"data":[5,59,131],"with":[6,93,120,123,251,350],"predictive":[7],"capabilities":[8],"for":[9,66,325],"numerical":[10],"targets":[11],"typically":[12],"requires":[13],"dimension":[14,37,379],"reduction":[15,38,380],"techniques":[16],"to":[17,106,128,297,371],"overcome":[18,74],"the":[19,42,51,58,67,117,124,135,143,147,190,195,199,237,248,268,274,309,354],"severe":[20],"curse":[21],"of":[22,41,57,69,99,149,164,189,194,198,239,262,273,292,304,344,356],"dimensionality":[23],"effects.":[24],"Linear":[25],"projection":[26],"methods":[27],"are":[28,61,158,204,279],"promising":[29],"candidates":[30],"in":[31,77,126,162,206,247,302],"this":[32,75,78],"context":[33],"as":[34,154,322],"they-unlike":[35],"nonlinear":[36],"techniques-preserve":[39],"interpretability":[40],"resulting":[43],"models.":[44],"However,":[45],"linear":[46],"projections":[47],"do":[48],"not":[49,63],"reveal":[50],"inherent":[52],"(nonlinear,":[53],"local)":[54],"cluster":[55],"structure":[56,96,172,327],"and":[60,218,295,307,312,359,382],"thus":[62],"ideally":[64],"suited":[65],"identification":[68],"rule":[71],"bases.":[72],"To":[73,230],"limitation,":[76],"article,":[79],"we":[80],"present":[81],"a":[82,94,112,180,232,240,282,289,342],"new":[83,181,318],"modeling":[85,92,348,375],"approach":[86,110,319],"that":[87],"combines":[88],"generalized":[89,165,241],"systems":[91],"local":[95,130,156,171,215,227,314,326],"preserving":[97,173,328],"variant":[98],"partial":[100],"least":[101],"squares":[102],"(PLS).":[103],"In":[104],"contrast":[105],"ordinary":[107],"PLS,":[108],"our":[109],"maps":[111],"weighted":[113,284],"(adjacency)":[114],"graph":[115],"on":[116,336],"directions":[118],"associated":[119],"high":[121],"covariance":[122],"response":[125],"order":[127],"emphasize":[129],"structures":[132],"when":[133,383],"constructing":[134],"latent":[136],"variable":[137,226],"(LV)":[138],"space.":[139,276],"This":[140],"operates":[141],"into":[142],"direction":[144],"which":[146,185],"(training":[148],"the)":[150],"model":[152,244,368],"benefits,":[153],"therein":[155],"regions":[157,203,221],"represented":[159],"by":[160,178,192,223,257,281],"submodels":[161],"form":[163],"Takagi-Sugeno":[166],"(TS)":[167],"rules.":[169,390],"The":[170,317],"LV":[174,249],"space":[175,250],"is":[176,245,255,320],"obtained":[177],"solving":[179],"penalized":[182],"objective":[183],"function,":[184],"assures":[186],"global":[187],"optimality":[188],"solutions":[191,300],"virtue":[193],"specific":[196],"properties":[197],"Laplacian":[200],"matrix.":[201],"Local":[202],"characterized":[205],"two":[207],"ways:":[208],"through":[209,219],"nearest":[210],"neighbor":[211],"points":[212],"(assuming":[213],"fixed":[214],"region":[216,228],"sizes)":[217],"density":[220],"identified":[222],"clustering":[224],"(achieving":[225],"sizes).":[229],"establish":[231],"robust":[233,260,299],"time-series-based":[234,346],"forecast":[235],"model,":[236],"training":[238,357],"TS":[242],"conducted":[246],"reduced":[252],"dimensionality.":[253,362],"It":[254,332],"realized":[256],"an":[258,377],"iterative":[259],"version":[261],"Gen-Smart-EFS,":[263],"allowing":[264],"multiple":[265],"passes":[266],"over":[267],"complete":[269],"datasets":[270],"until":[271],"convergence":[272],"antecedent":[275],"Consequent":[277],"parameters":[278],"estimated":[280],"fuzzily":[283],"elastic":[285],"net":[286],"approach,":[287],"embedding":[288],"convex":[290],"combination":[291],"ridge":[293],"regression":[294],"Lasso":[296],"achieve":[298],"also":[301],"case":[303],"ill-posed":[305],"problems":[306,349],"meeting":[308],"(more":[310],"stable":[311],"interpretable)":[313],"learning":[315],"spirit.":[316],"termed":[321],"LS-PLS-Fuzzy,":[323],"short":[324],"PLS":[329,386],"regression.":[331],"was":[333],"successfully":[334],"evaluated":[335],"three":[337],"real-world":[338],"application":[339],"scenarios":[340],"including":[341],"total":[343],"11":[345],"prediction":[347],"different":[351],"proportions":[352],"between":[353],"number":[355],"samples":[358],"original":[360],"input":[361],"Our":[363],"results":[364],"show":[365],"significantly":[366],"improved":[367],"accuracy":[369],"compared":[370],"related":[372],"State-of-the-Art":[373],"(SoA)":[374],"approaches,":[376],"alternative":[378],"technique,":[381],"using":[384],"conventional":[385],"and/or":[387],"nongeneralized":[388]},"counts_by_year":[{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
