{"id":"https://openalex.org/W2782918262","doi":"https://doi.org/10.1504/ijwmc.2017.10010308","title":"Analysis on fast training speed of extreme learning machine and replacement policy","display_name":"Analysis on fast training speed of extreme learning machine and replacement policy","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2782918262","doi":"https://doi.org/10.1504/ijwmc.2017.10010308","mag":"2782918262"},"language":"en","primary_location":{"id":"doi:10.1504/ijwmc.2017.10010308","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijwmc.2017.10010308","pdf_url":null,"source":{"id":"https://openalex.org/S168395412","display_name":"International Journal of Wireless and Mobile Computing","issn_l":"1741-1084","issn":["1741-1084","1741-1092"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wireless and Mobile Computing","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/A5112520247","display_name":"Li Ying Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I90090648","display_name":"Shijiazhuang Tiedao University","ror":"https://ror.org/022e9e065","country_code":"CN","type":"education","lineage":["https://openalex.org/I90090648"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Li Ying Wang","raw_affiliation_strings":["Department of Mathematics and Physics, Shijiazhuang Tiedao University, Shijiazhuang 050043, China"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Physics, Shijiazhuang Tiedao University, Shijiazhuang 050043, China","institution_ids":["https://openalex.org/I90090648"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101030797","display_name":"Jun Mei Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I90090648","display_name":"Shijiazhuang Tiedao University","ror":"https://ror.org/022e9e065","country_code":"CN","type":"education","lineage":["https://openalex.org/I90090648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Mei Hu","raw_affiliation_strings":["Department of Mathematics and Physics, Shijiazhuang Tiedao University, Shijiazhuang 050043, China"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics and Physics, Shijiazhuang Tiedao University, Shijiazhuang 050043, China","institution_ids":["https://openalex.org/I90090648"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064994372","display_name":"Xi Zhao Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xi Zhao Wang","raw_affiliation_strings":["College of Computer Science and Soft Engineering, Shenzhen University, Shenzhen 518060, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Soft Engineering, Shenzhen University, Shenzhen 518060, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100415567","display_name":"Wei-Ping Li","orcid":"https://orcid.org/0009-0009-1724-6115"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Ping Li","raw_affiliation_strings":["School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China"],"affiliations":[{"raw_affiliation_string":"School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078835371","display_name":"Shi Xin Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I90090648","display_name":"Shijiazhuang Tiedao University","ror":"https://ror.org/022e9e065","country_code":"CN","type":"education","lineage":["https://openalex.org/I90090648"]},{"id":"https://openalex.org/I43337087","display_name":"Hebei University","ror":"https://ror.org/01p884a79","country_code":"CN","type":"education","lineage":["https://openalex.org/I43337087"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shi Xin Zhao","raw_affiliation_strings":["College of Management, Hebei University, Baoding 071002, China; Department of Mathematics and Physics, Shijiazhuang Tiedao University, Shijiazhuang 050043, China","College of Management, Hebei University, Baoding 071002, China","Department of Mathematics and Physics, Shijiazhuang Tiedao University, Shijiazhuang 050043, China"],"affiliations":[{"raw_affiliation_string":"College of Management, Hebei University, Baoding 071002, China; Department of Mathematics and Physics, Shijiazhuang Tiedao University, Shijiazhuang 050043, China","institution_ids":["https://openalex.org/I90090648"]},{"raw_affiliation_string":"College of Management, Hebei University, Baoding 071002, China","institution_ids":["https://openalex.org/I43337087"]},{"raw_affiliation_string":"Department of Mathematics and Physics, Shijiazhuang Tiedao University, Shijiazhuang 050043, China","institution_ids":["https://openalex.org/I90090648"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5112520247"],"corresponding_institution_ids":["https://openalex.org/I90090648"],"apc_list":null,"apc_paid":null,"fwci":0.195,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.64705367,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"13","issue":"4","first_page":"314","last_page":"314"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":1.0,"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":1.0,"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":0.9919000267982483,"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"}},{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","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"}}],"keywords":[{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.8116704821586609},{"id":"https://openalex.org/keywords/inverse","display_name":"Inverse","score":0.7430321574211121},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7340104579925537},{"id":"https://openalex.org/keywords/conjugate-gradient-method","display_name":"Conjugate gradient method","score":0.6992504000663757},{"id":"https://openalex.org/keywords/speedup","display_name":"Speedup","score":0.6314944624900818},{"id":"https://openalex.org/keywords/singular-value-decomposition","display_name":"Singular value decomposition","score":0.6038894057273865},{"id":"https://openalex.org/keywords/moore\u2013penrose-pseudoinverse","display_name":"Moore\u2013Penrose pseudoinverse","score":0.5747835636138916},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5286104083061218},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.43323689699172974},{"id":"https://openalex.org/keywords/generalized-inverse","display_name":"Generalized inverse","score":0.41609811782836914},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3458898365497589},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3237811028957367},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2322094738483429},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1668114960193634},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.10966786742210388},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.07217186689376831}],"concepts":[{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.8116704821586609},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.7430321574211121},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7340104579925537},{"id":"https://openalex.org/C81184566","wikidata":"https://www.wikidata.org/wiki/Q1191895","display_name":"Conjugate gradient method","level":2,"score":0.6992504000663757},{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6314944624900818},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.6038894057273865},{"id":"https://openalex.org/C21556879","wikidata":"https://www.wikidata.org/wiki/Q43219517","display_name":"Moore\u2013Penrose pseudoinverse","level":3,"score":0.5747835636138916},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5286104083061218},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.43323689699172974},{"id":"https://openalex.org/C76134657","wikidata":"https://www.wikidata.org/wiki/Q370634","display_name":"Generalized inverse","level":3,"score":0.41609811782836914},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3458898365497589},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3237811028957367},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2322094738483429},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1668114960193634},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.10966786742210388},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.07217186689376831},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1504/ijwmc.2017.10010308","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijwmc.2017.10010308","pdf_url":null,"source":{"id":"https://openalex.org/S168395412","display_name":"International Journal of Wireless and Mobile Computing","issn_l":"1741-1084","issn":["1741-1084","1741-1092"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Wireless and Mobile Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W324638355","https://openalex.org/W1566309885","https://openalex.org/W1643510495","https://openalex.org/W1965895201","https://openalex.org/W2017522944","https://openalex.org/W2040604977","https://openalex.org/W2043430160","https://openalex.org/W2077611589","https://openalex.org/W2087070363","https://openalex.org/W2099579348","https://openalex.org/W2108263314","https://openalex.org/W2111072639","https://openalex.org/W2117941247","https://openalex.org/W2134603844","https://openalex.org/W2136602355","https://openalex.org/W2175372401","https://openalex.org/W2286961399","https://openalex.org/W2294821210","https://openalex.org/W2316564661","https://openalex.org/W2464625730","https://openalex.org/W2558662207","https://openalex.org/W2569507235","https://openalex.org/W3099056690"],"related_works":["https://openalex.org/W4308535303","https://openalex.org/W4224249946","https://openalex.org/W4206885134","https://openalex.org/W2464262491","https://openalex.org/W3165869240","https://openalex.org/W2790733271","https://openalex.org/W2739280734","https://openalex.org/W3096132384","https://openalex.org/W4287606346","https://openalex.org/W4385197416"],"abstract_inverted_index":{"Extreme":[0],"learning":[1,8,15,118,192],"machine":[2],"is":[3,59,124,139,186],"known":[4],"for":[5],"its":[6,75],"fast":[7,76,191],"speed":[9,119,151,193],"while":[10],"maintaining":[11,158],"acceptable":[12],"generalisation.":[13,160],"Its":[14],"process":[16],"can":[17],"be":[18],"divided":[19],"into":[20],"two":[21],"parts:":[22],"(1)":[23],"randomly":[24],"assigns":[25],"input":[26],"weights":[27,38,62],"and":[28,33,51,106,133],"biases":[29],"in":[30,145,154,162],"hidden":[31,87],"layer,":[32],"(2)":[34],"analytically":[35],"determines":[36],"output":[37,89],"by":[39],"the":[40,47,60,66,81,117,155,163,171,188],"use":[41],"of":[42,83,86,120,129,157,170,174,190,194],"Moore-Penrose":[43,130,183],"generalised":[44,70,84,131,184],"inverse.":[45],"Through":[46],"analysis":[48],"from":[49,196],"theory":[50],"experiment":[52,197],"aspects":[53],"we":[54],"point":[55],"out":[56],"that":[57,72,165,182],"it":[58],"random":[61],"assignment":[63],"rather":[64],"than":[65,152],"analytical":[67],"determination":[68],"with":[69],"inverse":[71,85,132,185],"leads":[73],"to":[74],"training":[77],"speed.":[78],"In":[79],"fact,":[80],"calculation":[82,114],"layer":[88],"matrix":[90],"based":[91,136],"on":[92,102],"singular":[93],"value":[94],"decomposition":[95],"(SVD)":[96],"has":[97],"very":[98],"low":[99],"efficiency":[100],"especially":[101],"large":[103],"scale":[104],"data,":[105],"even":[107],"directly":[108],"cannot":[109,167],"work.":[110],"Considering":[111],"this":[112],"high":[113],"complexity":[115],"reduces":[116],"ELM":[121,137,153,166,195],"conjugate":[122,134],"gradient":[123,135],"introduced":[125],"as":[126],"a":[127],"replacement":[128],"(CG-ELM)":[138],"proposed.":[140],"Numerical":[141],"simulations":[142],"show":[143],"that,":[144],"most":[146],"cases,":[147],"CG-ELM":[148,176],"achieved":[149],"faster":[150],"condition":[156],"similar":[159],"Even":[161],"case":[164],"work":[168],"because":[169],"huge":[172],"amount":[173],"data":[175],"attains":[177],"good":[178],"performance,":[179],"which":[180],"illustrates":[181],"not":[187],"contribution":[189],"view.":[198]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
