{"id":"https://openalex.org/W2884138578","doi":"https://doi.org/10.3906/elk-1706-60","title":"Optimum, projected, and regularized extreme learning machine methods with singular value decomposition and L 2 -Tikhonov regularization","display_name":"Optimum, projected, and regularized extreme learning machine methods with singular value decomposition and L 2 -Tikhonov regularization","publication_year":2018,"publication_date":"2018-07-27","ids":{"openalex":"https://openalex.org/W2884138578","doi":"https://doi.org/10.3906/elk-1706-60","mag":"2884138578"},"language":"en","primary_location":{"id":"doi:10.3906/elk-1706-60","is_oa":true,"landing_page_url":"http://doi.org/10.3906/elk-1706-60","pdf_url":"https://doi.org/10.3906/elk-1706-60","source":{"id":"https://openalex.org/S32837994","display_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","issn_l":"1300-0632","issn":["1300-0632","1303-6203"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318422","host_organization_name":"Scientific and Technological Research Council of Turkey (TUBITAK)","host_organization_lineage":["https://openalex.org/P4310318422"],"host_organization_lineage_names":["Scientific and Technological Research Council of Turkey (TUBITAK)"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://doi.org/10.3906/elk-1706-60","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022251520","display_name":"Mohanad Abd Shehab","orcid":"https://orcid.org/0000-0002-2941-0762"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mohanad Abd SHEHAB","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5001264241","display_name":"Nihan Kahraman","orcid":"https://orcid.org/0000-0003-1623-3557"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nihan KAHRAMAN","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5022251520"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.07872407,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"26","issue":"4","first_page":"1685","last_page":"1697"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9998999834060669,"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/T12676","display_name":"Machine Learning and ELM","score":0.9998999834060669,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9793000221252441,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9674000144004822,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/tikhonov-regularization","display_name":"Tikhonov regularization","score":0.7857047915458679},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.7642583250999451},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.630614697933197},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5917266607284546},{"id":"https://openalex.org/keywords/early-stopping","display_name":"Early stopping","score":0.5744556188583374},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.545674204826355},{"id":"https://openalex.org/keywords/singular-value","display_name":"Singular value","score":0.5329751968383789},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.5309633016586304},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.5160171985626221},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.46253231167793274},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.43742942810058594},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.42845454812049866},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4053995609283447},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.27931371331214905},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.23905795812606812},{"id":"https://openalex.org/keywords/inverse-problem","display_name":"Inverse problem","score":0.1881406605243683},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.14837729930877686}],"concepts":[{"id":"https://openalex.org/C152442038","wikidata":"https://www.wikidata.org/wiki/Q2778212","display_name":"Tikhonov regularization","level":3,"score":0.7857047915458679},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.7642583250999451},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.630614697933197},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5917266607284546},{"id":"https://openalex.org/C5465570","wikidata":"https://www.wikidata.org/wiki/Q5326898","display_name":"Early stopping","level":3,"score":0.5744556188583374},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.545674204826355},{"id":"https://openalex.org/C109282560","wikidata":"https://www.wikidata.org/wiki/Q4166054","display_name":"Singular value","level":3,"score":0.5329751968383789},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.5309633016586304},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.5160171985626221},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.46253231167793274},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.43742942810058594},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42845454812049866},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4053995609283447},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.27931371331214905},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.23905795812606812},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.1881406605243683},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.14837729930877686},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3906/elk-1706-60","is_oa":true,"landing_page_url":"http://doi.org/10.3906/elk-1706-60","pdf_url":"https://doi.org/10.3906/elk-1706-60","source":{"id":"https://openalex.org/S32837994","display_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","issn_l":"1300-0632","issn":["1300-0632","1303-6203"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318422","host_organization_name":"Scientific and Technological Research Council of Turkey (TUBITAK)","host_organization_lineage":["https://openalex.org/P4310318422"],"host_organization_lineage_names":["Scientific and Technological Research Council of Turkey (TUBITAK)"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","raw_type":"journal-article"},{"id":"pmh:oai:dergipark.org.tr:article/574317","is_oa":false,"landing_page_url":"https://dergipark.org.tr/tr/pub/tbtkelektrik/issue/45628/574317","pdf_url":null,"source":{"id":"https://openalex.org/S4306401840","display_name":"DergiPark (Istanbul University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67581229","host_organization_name":"Istanbul University","host_organization_lineage":["https://openalex.org/I67581229"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"\\n                                                                    Volume: 26, Issue: 4\\n                                                                                                    1685-1697\\n                                                                \\n                            ","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.3906/elk-1706-60","is_oa":true,"landing_page_url":"http://doi.org/10.3906/elk-1706-60","pdf_url":"https://doi.org/10.3906/elk-1706-60","source":{"id":"https://openalex.org/S32837994","display_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","issn_l":"1300-0632","issn":["1300-0632","1303-6203"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318422","host_organization_name":"Scientific and Technological Research Council of Turkey (TUBITAK)","host_organization_lineage":["https://openalex.org/P4310318422"],"host_organization_lineage_names":["Scientific and Technological Research Council of Turkey (TUBITAK)"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2884138578.pdf","grobid_xml":"https://content.openalex.org/works/W2884138578.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2373436489","https://openalex.org/W4319586039","https://openalex.org/W4382583540","https://openalex.org/W2147072251","https://openalex.org/W2148568324","https://openalex.org/W1607100495","https://openalex.org/W4386721910","https://openalex.org/W4378770618","https://openalex.org/W3114212224","https://openalex.org/W2164147222"],"abstract_inverted_index":{"The":[0,150,182,215],"theory":[1],"and":[2,18,32,58,84,129,171,180,209,229,237,243,253,300],"implementation":[3],"of":[4,112,127,153,163,212,224,241,257,274],"an":[5,24,103],"extreme":[6],"learning":[7,21,302],"machine":[8,20],"(ELM)":[9],"have":[10],"proved":[11],"that":[12,101,108,200,261],"it":[13,245,267],"is":[14,45,60,75,246,268,288],"a":[15,76,82,195,279,294],"simple,":[16],"efficient,":[17],"accurate":[19],"methodology.":[22],"In":[23,79],"ELM,":[25],"the":[26,38,46,65,70,96,110,125,133,161,164,173,177,189,202,206,210,234,264,272,307],"hidden":[27,40,66,98,275],"nodes":[28,276],"are":[29],"randomly":[30],"initiated":[31],"fixed":[33],"without":[34],"iterative":[35,185],"tuning.":[36],"However,":[37],"optimal":[39],"layer":[41,67,99],"neuron":[42],"number":[43,55],"($L_{opt})$":[44],"key":[47],"to":[48,94,123,233,248,270,293],"ELM":[49,90,140,167,265],"generalization":[50],"performance":[51,266],"where":[52],"initializing":[53],"this":[54,80,154],"by":[56,193],"trial":[57],"error":[59,208],"not":[61],"reasonably":[62],"satisfied.":[63],"Optimizing":[64],"size":[68,100,273],"using":[69],"leave-one-out":[71],"cross":[72],"validation":[73],"method":[74],"costly":[77],"approach.":[78],"paper,":[81],"fast":[83],"reliable":[85],"statistical":[86],"approach":[87],"called":[88],"optimum":[89,104,190],"(OELM)":[91],"was":[92,119,156,218],"developed":[93],"determine":[95],"minimum":[97],"yields":[102],"performance.":[105],"Another":[106],"improvement":[107],"exploits":[109],"advantages":[111],"orthogonal":[113],"projections":[114],"with":[115,166,197,251,306],"singular":[116],"value":[117],"decomposition":[118],"proposed":[120,216,308],"in":[121,132,147,160,220,281,286],"order":[122],"tackle":[124],"problem":[126],"randomness":[128],"correlated":[130],"features":[131],"input":[134],"data.":[135,258],"This":[136],"approach,":[137],"named":[138],"projected":[139],"(PELM),":[141],"achieves":[142],"more":[143],"than":[144],"2{\\\\%}":[145],"advance":[146],"average":[148],"accuracy.":[149,296],"final":[151],"contribution":[152],"paper":[155],"implementing":[157],"Tikhonov":[158],"regularization":[159,191],"form":[162],"L$_{2}$-penalty":[165],"(TRELM),":[168],"which":[169,290],"regularizes":[170],"improves":[172],"matrix":[174],"computations":[175],"utilizing":[176],"L-curve":[178],"criterion":[179],"SVD.":[181],"L-curve,":[183],"unlike":[184],"methods,":[186],"can":[187],"estimate":[188],"parameter":[192],"illustrating":[194],"curve":[196],"few":[198],"points":[199],"represents":[201],"tradeoff":[203],"between":[204],"minimizing":[205],"training":[207],"residual":[211],"output":[213],"weight.":[214],"TRELM":[217,259,287],"tested":[219],"3":[221],"different":[222],"scenarios":[223],"data":[225],"sizes:":[226],"small,":[227],"moderate,":[228],"big":[230,282],"datasets.":[231],"Due":[232],"simplicity,":[235],"robustness,":[236],"less":[238],"time":[239],"consumption":[240],"OELM":[242],"PELM,":[244],"recommended":[247],"use":[249],"them":[250],"small":[252],"even":[254],"moderate":[255],"amounts":[256],"demonstrated":[260],"when":[262],"enhancing":[263],"necessary":[269],"enlarge":[271],"$(L)$.":[277],"As":[278],"result,":[280],"data,":[283],"increasing":[284],"$L$":[285],"necessary,":[289],"concurrently":[291],"leads":[292],"better":[295],"Various":[297],"well-known":[298],"datasets":[299],"state-of-the-art":[301],"approaches":[303],"were":[304],"compared":[305],"approaches.":[309]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}