{"id":"https://openalex.org/W2053908901","doi":"https://doi.org/10.1016/j.eswa.2010.06.092","title":"Artificial neural network based approach for dynamic parameter design","display_name":"Artificial neural network based approach for dynamic parameter design","publication_year":2010,"publication_date":"2010-07-07","ids":{"openalex":"https://openalex.org/W2053908901","doi":"https://doi.org/10.1016/j.eswa.2010.06.092","mag":"2053908901"},"language":"en","primary_location":{"id":"doi:10.1016/j.eswa.2010.06.092","doi":"https://doi.org/10.1016/j.eswa.2010.06.092","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.eswa.2010.06.092","pdf_url":null,"source":{"id":"https://openalex.org/S13144211","display_name":"Expert Systems with Applications","issn_l":"0957-4174","issn":["0957-4174","1873-6793"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-c","cwts-core","dongbi-c","doyens","fnege-3","jufo-2","ki-jl-2","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Expert Systems with Applications","raw_type":"journal-article"},"volume":null,"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/A5080815741","display_name":"Jae-Ryung Jung","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jae-Ryung Jung","raw_affiliation_strings":["Department of Industrial and Systems Engineering, KAIST, 373-1 Gusung-Dong, Yusung-Gu, Taejon 305-701, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, KAIST, 373-1 Gusung-Dong, Yusung-Gu, Taejon 305-701, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111581529","display_name":"Bong\u2010Jin Yum","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Bong-Jin Yum","raw_affiliation_strings":["Department of Industrial and Systems Engineering, KAIST, 373-1 Gusung-Dong, Yusung-Gu, Taejon 305-701, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Industrial and Systems Engineering, KAIST, 373-1 Gusung-Dong, Yusung-Gu, Taejon 305-701, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5111581529"],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":{"value":3500,"currency":"USD","value_usd":3500},"apc_paid":null,"fwci":2.1797,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.88370096,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"38","issue":"1","first_page":"504","last_page":"510"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11798","display_name":"Optimal Experimental Design Methods","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10928","display_name":"Probabilistic and Robust Engineering Design","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":9.999999747378752e-05,"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/taguchi-parameter-design","display_name":"Taguchi parameter design","score":0.8429999947547913},{"id":"https://openalex.org/keywords/neural-network","display_name":"artificial neural networks","score":0.9269999861717224},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"signal-to-noise ratio","score":0.7620000243186951},{"id":"https://openalex.org/keywords/noise-parameters","display_name":"noise parameters","score":0.7089999914169312},{"id":"https://openalex.org/keywords/latin-hypercube-sampling","display_name":"Latin hypercube sampling","score":0.7639999985694885},{"id":"https://openalex.org/keywords/nonlinear-programming","display_name":"nonlinear programming","score":0.6840000152587891},{"id":"https://openalex.org/keywords/sequential-quadratic-programming","display_name":"sequential quadratic programming","score":0.9789999723434448},{"id":"https://openalex.org/keywords/quality-engineering","display_name":"quality engineering","score":0.49000000953674316}],"concepts":[{"id":"https://openalex.org/C83469408","wikidata":"https://www.wikidata.org/wiki/Q2036525","display_name":"Taguchi methods","level":2,"score":0.8938874006271362},{"id":"https://openalex.org/C20820323","wikidata":"https://www.wikidata.org/wiki/Q6496514","display_name":"Latin hypercube sampling","level":3,"score":0.66899573802948},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6419536471366882},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6415486931800842},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.5676187872886658},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.5329433679580688},{"id":"https://openalex.org/C34559072","wikidata":"https://www.wikidata.org/wiki/Q2334061","display_name":"Design of experiments","level":2,"score":0.5200338363647461},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4997546672821045},{"id":"https://openalex.org/C42632107","wikidata":"https://www.wikidata.org/wiki/Q2031860","display_name":"Orthogonal array","level":3,"score":0.42364501953125},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3375709056854248},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26351797580718994},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.20907533168792725},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.20183873176574707},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15284273028373718},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.12961816787719727},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1016/j.eswa.2010.06.092","doi":"https://doi.org/10.1016/j.eswa.2010.06.092","is_oa":false,"landing_page_url":"https://doi.org/10.1016/j.eswa.2010.06.092","pdf_url":null,"source":{"id":"https://openalex.org/S13144211","display_name":"Expert Systems with Applications","issn_l":"0957-4174","issn":["0957-4174","1873-6793"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","ccf-c","cwts-core","dongbi-c","doyens","fnege-3","jufo-2","ki-jl-2","norway-2","poland-200","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Expert Systems with Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W17851708","https://openalex.org/W156343950","https://openalex.org/W1513595735","https://openalex.org/W1825077972","https://openalex.org/W1967652398","https://openalex.org/W1971735090","https://openalex.org/W1977996087","https://openalex.org/W2013196027","https://openalex.org/W2014171953","https://openalex.org/W2018044188","https://openalex.org/W2025571610","https://openalex.org/W2026048962","https://openalex.org/W2039247302","https://openalex.org/W2039708501","https://openalex.org/W2045059345","https://openalex.org/W2078182939","https://openalex.org/W2090514762","https://openalex.org/W2101927907","https://openalex.org/W2105594594","https://openalex.org/W2149416133","https://openalex.org/W2151025666","https://openalex.org/W2153446897","https://openalex.org/W4247680473","https://openalex.org/W4253147876","https://openalex.org/W4300307554"],"related_works":["https://openalex.org/W256217178","https://openalex.org/W865863276","https://openalex.org/W2026454263","https://openalex.org/W2120828841","https://openalex.org/W1967109380","https://openalex.org/W1986780253","https://openalex.org/W2045059345","https://openalex.org/W2125414332","https://openalex.org/W244352405","https://openalex.org/W2078182939"],"abstract_inverted_index":null,"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":2}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-06-24T00:00:00"}
