{"id":"https://openalex.org/W2739821268","doi":"https://doi.org/10.4018/ijiit.2017100103","title":"Designing Extreme Learning Machine Network Structure Based on Tolerance Rough Set","display_name":"Designing Extreme Learning Machine Network Structure Based on Tolerance Rough Set","publication_year":2017,"publication_date":"2017-08-01","ids":{"openalex":"https://openalex.org/W2739821268","doi":"https://doi.org/10.4018/ijiit.2017100103","mag":"2739821268"},"language":"en","primary_location":{"id":"doi:10.4018/ijiit.2017100103","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijiit.2017100103","pdf_url":null,"source":{"id":"https://openalex.org/S116626079","display_name":"International Journal of Intelligent Information Technologies","issn_l":"1548-3657","issn":["1548-3657","1548-3665"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Information Technologies","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/A5091062044","display_name":"Ke Han","orcid":"https://orcid.org/0000-0001-7839-6584"},"institutions":[{"id":"https://openalex.org/I198645480","display_name":"North China University of Water Resources and Electric Power","ror":"https://ror.org/03acrzv41","country_code":"CN","type":"education","lineage":["https://openalex.org/I198645480"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Han Ke","raw_affiliation_strings":["North China University of Water Resources and Electric Power, Zhengzhou, China"],"affiliations":[{"raw_affiliation_string":"North China University of Water Resources and Electric Power, Zhengzhou, China","institution_ids":["https://openalex.org/I198645480"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5091062044"],"corresponding_institution_ids":["https://openalex.org/I198645480"],"apc_list":null,"apc_paid":null,"fwci":0.39,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.69993187,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"13","issue":"4","first_page":"38","last_page":"55"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9995999932289124,"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":0.9995999932289124,"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":0.9886999726295471,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9843999743461609,"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/rough-set","display_name":"Rough set","score":0.8630469441413879},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8244747519493103},{"id":"https://openalex.org/keywords/extreme-learning-machine","display_name":"Extreme learning machine","score":0.702437162399292},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5930256843566895},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5405738353729248},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5291892290115356},{"id":"https://openalex.org/keywords/basis","display_name":"Basis (linear algebra)","score":0.5234624743461609},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4926465153694153},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4862474203109741},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.26905113458633423},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1170874834060669}],"concepts":[{"id":"https://openalex.org/C111012933","wikidata":"https://www.wikidata.org/wiki/Q3137210","display_name":"Rough set","level":2,"score":0.8630469441413879},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8244747519493103},{"id":"https://openalex.org/C2780150128","wikidata":"https://www.wikidata.org/wiki/Q21948731","display_name":"Extreme learning machine","level":3,"score":0.702437162399292},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5930256843566895},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5405738353729248},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5291892290115356},{"id":"https://openalex.org/C12426560","wikidata":"https://www.wikidata.org/wiki/Q189569","display_name":"Basis (linear algebra)","level":2,"score":0.5234624743461609},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4926465153694153},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4862474203109741},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.26905113458633423},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1170874834060669},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4018/ijiit.2017100103","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijiit.2017100103","pdf_url":null,"source":{"id":"https://openalex.org/S116626079","display_name":"International Journal of Intelligent Information Technologies","issn_l":"1548-3657","issn":["1548-3657","1548-3665"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Intelligent Information Technologies","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:igg:jiit00:v:13:y:2017:i:4:p:38-55","is_oa":false,"landing_page_url":"https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJIIT.2017100103","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6700000166893005,"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W430601014","https://openalex.org/W1983955072","https://openalex.org/W2014267653","https://openalex.org/W2018675859","https://openalex.org/W2032680755","https://openalex.org/W2035309212","https://openalex.org/W2042593695","https://openalex.org/W2058128874","https://openalex.org/W2062163504","https://openalex.org/W2063414811","https://openalex.org/W2086075853","https://openalex.org/W2088654600","https://openalex.org/W2088920913","https://openalex.org/W2121971770","https://openalex.org/W2158054309","https://openalex.org/W2160512933","https://openalex.org/W2240504034","https://openalex.org/W2381386908","https://openalex.org/W2385915903","https://openalex.org/W2543461915"],"related_works":["https://openalex.org/W2067443264","https://openalex.org/W2969890106","https://openalex.org/W2369031945","https://openalex.org/W1985015628","https://openalex.org/W2204496524","https://openalex.org/W2388587252","https://openalex.org/W2354040054","https://openalex.org/W2905251838","https://openalex.org/W2350442377","https://openalex.org/W1970534408"],"abstract_inverted_index":{"In":[0],"this":[1,22],"paper,":[2],"we":[3],"present":[4],"a":[5,48],"new":[6,50],"extreme":[7],"learning":[8],"machine":[9],"network":[10,32],"structure":[11],"on":[12],"the":[13,27,74,79,85,93,99,108],"basis":[14],"of":[15,21,78,84,87,110],"tolerance":[16],"rough":[17,45],"set.":[18],"The":[19,81],"purpose":[20],"paper":[23],"is":[24,47,104],"to":[25,40,55,106],"realize":[26],"high-efficiency":[28],"and":[29,69,72,76,89],"multi-dimensional":[30],"ELM":[31],"structure.":[33],"Various":[34],"published":[35],"algorithms":[36],"have":[37],"been":[38],"applied":[39],"breast":[41,57],"cancer":[42,58],"datasets,":[43],"but":[44],"set":[46],"fairly":[49],"intelligent":[51],"technique":[52],"that":[53,92],"applies":[54],"predict":[56],"recurrence.":[59],"We":[60],"analyze":[61],"Ljubljana":[62],"Breast":[63],"Cancer":[64],"Dataset,":[65],"firstly,":[66],"obtain":[67],"lower":[68],"upper":[70],"approximations":[71],"calculate":[73],"accuracy":[75,90],"quality":[77,86],"classification.":[80,100],"high":[82],"values":[83],"classification":[88],"prove":[91],"attributes":[94],"selected":[95],"can":[96],"well":[97],"approximate":[98],"Rough":[101],"sets":[102],"approach":[103],"established":[105],"solve":[107],"prolem":[109],"tolerance.":[111]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}