{"id":"https://openalex.org/W3084335858","doi":"https://doi.org/10.1109/access.2020.3022627","title":"Enhanced Kernel-Based Multilayer Fuzzy Weighted Extreme Learning Machines","display_name":"Enhanced Kernel-Based Multilayer Fuzzy Weighted Extreme Learning Machines","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3084335858","doi":"https://doi.org/10.1109/access.2020.3022627","mag":"3084335858"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3022627","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3022627","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09187885.pdf","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":null,"license_id":null,"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://ieeexplore.ieee.org/ielx7/6287639/8948470/09187885.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100714572","display_name":"Yang Wang","orcid":"https://orcid.org/0000-0001-8656-5405"},"institutions":[{"id":"https://openalex.org/I166846921","display_name":"Liaoning Shihua University","ror":"https://ror.org/00k6c4h29","country_code":"CN","type":"education","lineage":["https://openalex.org/I166846921"]},{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Wang","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, Shenyang, China","School of Computer and Communication Engineering, Liaoning Shihua University, Fushun, China"],"raw_orcid":"https://orcid.org/0000-0001-8656-5405","affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]},{"raw_affiliation_string":"School of Computer and Communication Engineering, Liaoning Shihua University, Fushun, China","institution_ids":["https://openalex.org/I166846921"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043482575","display_name":"Anna Wang","orcid":"https://orcid.org/0000-0001-9905-767X"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"An-Na Wang","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032765483","display_name":"Qing Ai","orcid":"https://orcid.org/0000-0002-8081-6805"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qing Ai","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":"https://orcid.org/0000-0002-8081-6805","affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113112024","display_name":"Haijing Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hai-Jing Sun","raw_affiliation_strings":["College of Information Science and Engineering, Northeastern University, Shenyang, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Northeastern University, Shenyang, China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.2608,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.63592514,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"8","issue":null,"first_page":"166246","last_page":"166260"},"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/T10057","display_name":"Face and Expression Recognition","score":0.9679999947547913,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10100","display_name":"Metaheuristic Optimization Algorithms Research","score":0.9556999802589417,"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/computer-science","display_name":"Computer science","score":0.7602326273918152},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.7406333684921265},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6833840012550354},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6701212525367737},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5919667482376099},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5855749845504761},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5634703636169434},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.4626155495643616},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46195247769355774},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.4399195909500122},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4325682520866394},{"id":"https://openalex.org/keywords/multiple-kernel-learning","display_name":"Multiple kernel learning","score":0.42003610730171204},{"id":"https://openalex.org/keywords/incremental-learning","display_name":"Incremental learning","score":0.41928496956825256},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.3651356101036072},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3639678359031677},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.2850465178489685},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2840784788131714},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13058632612228394}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7602326273918152},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.7406333684921265},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6833840012550354},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6701212525367737},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5919667482376099},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5855749845504761},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5634703636169434},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.4626155495643616},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46195247769355774},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.4399195909500122},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4325682520866394},{"id":"https://openalex.org/C2776879701","wikidata":"https://www.wikidata.org/wiki/Q25048660","display_name":"Multiple kernel learning","level":4,"score":0.42003610730171204},{"id":"https://openalex.org/C2780735816","wikidata":"https://www.wikidata.org/wiki/Q28324931","display_name":"Incremental learning","level":2,"score":0.41928496956825256},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3651356101036072},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3639678359031677},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.2850465178489685},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2840784788131714},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13058632612228394},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3022627","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3022627","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09187885.pdf","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:c9c90760a6bb462eba082287390c3b9c","is_oa":true,"landing_page_url":"https://doaj.org/article/c9c90760a6bb462eba082287390c3b9c","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 8, Pp 166246-166260 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3022627","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3022627","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09187885.pdf","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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3084335858.pdf","grobid_xml":"https://content.openalex.org/works/W3084335858.grobid-xml"},"referenced_works_count":41,"referenced_works":["https://openalex.org/W1783902599","https://openalex.org/W1874498466","https://openalex.org/W1983364832","https://openalex.org/W1984530193","https://openalex.org/W1994807229","https://openalex.org/W2002302337","https://openalex.org/W2026131661","https://openalex.org/W2038523443","https://openalex.org/W2053961820","https://openalex.org/W2061438946","https://openalex.org/W2064528384","https://openalex.org/W2065186919","https://openalex.org/W2076063813","https://openalex.org/W2076637413","https://openalex.org/W2078622091","https://openalex.org/W2099579348","https://openalex.org/W2100495367","https://openalex.org/W2104167780","https://openalex.org/W2105577021","https://openalex.org/W2111072639","https://openalex.org/W2118978333","https://openalex.org/W2119191234","https://openalex.org/W2139212933","https://openalex.org/W2145094598","https://openalex.org/W2148143831","https://openalex.org/W2152195021","https://openalex.org/W2163922914","https://openalex.org/W2238314517","https://openalex.org/W2345827752","https://openalex.org/W2408157549","https://openalex.org/W2560323025","https://openalex.org/W2561964848","https://openalex.org/W2590739781","https://openalex.org/W2615743202","https://openalex.org/W2739807715","https://openalex.org/W2751647243","https://openalex.org/W2898207304","https://openalex.org/W2997574889","https://openalex.org/W4231109964","https://openalex.org/W6675770872","https://openalex.org/W6681096077"],"related_works":["https://openalex.org/W1986096622","https://openalex.org/W2900715739","https://openalex.org/W2289496068","https://openalex.org/W2043864454","https://openalex.org/W2547116720","https://openalex.org/W2188831877","https://openalex.org/W2157356416","https://openalex.org/W3125885229","https://openalex.org/W1483460610","https://openalex.org/W2828181497"],"abstract_inverted_index":{"The":[0],"high-dimensional":[1,156],"and":[2,79,97,114,136,150,157],"imbalanced":[3,158],"data":[4],"classification":[5,61,74,115],"appears":[6],"in":[7,17,43],"many":[8,14],"actual":[9],"applications,":[10],"but":[11],"there":[12],"are":[13,131],"problems":[15],"encountered":[16],"practical":[18],"operation.":[19],"To":[20],"overcome":[21],"the":[22,60,64,94,99,106,144,155],"disadvantages":[23],"of":[24,63,102,108],"kernel-based":[25,32],"multilayer":[26,33],"extreme":[27,36],"learning":[28,37,113,122],"machines":[29,38],"(ML-KELM),":[30],"enhanced":[31,86],"fuzzy":[34,70],"weighted":[35,54],"(EML-KFWELM)":[39],"has":[40,147],"been":[41],"proposed":[42,145],"this":[44],"study.":[45],"First,":[46],"ML-KELM":[47,57],"ignores":[48],"imbalance":[49],"learning,":[50],"so":[51],"we":[52,68,83],"embed":[53],"strategy":[55],"into":[56,119],"to":[58,72,92],"enhance":[59],"performance":[62,101],"minority":[65],"class.":[66],"Meanwhile,":[67],"propose":[69],"membership":[71],"eliminate":[73],"error":[75],"caused":[76],"by":[77],"outlier":[78],"noise":[80],"samples.":[81],"Furthermore,":[82],"develop":[84],"an":[85],"grey":[87],"wolf":[88],"optimization":[89,96],"(EGWO)":[90],"method":[91],"perform":[93],"parameters":[95],"improve":[98],"generalization":[100],"ML-KELM.":[103],"In":[104],"addition,":[105],"advantage":[107],"EML-KFWELM":[109,146],"is":[110],"that":[111,143],"representation":[112],"can":[116,151],"be":[117],"integrated":[118],"a":[120],"single":[121],"process.":[123],"Finally,":[124],"computational":[125],"comparisons":[126],"with":[127,154],"other":[128],"state-of-the-art":[129],"methods":[130],"performed":[132],"on":[133],"various":[134],"real-world":[135],"gene":[137],"expression":[138],"data.":[139,159],"Experimental":[140],"results":[141],"demonstrate":[142],"good":[148],"stability":[149],"efficiently":[152],"deal":[153]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
