{"@context":{"@vocab":"https://cir.nii.ac.jp/schema/1.0/","rdfs":"http://www.w3.org/2000/01/rdf-schema#","dc":"http://purl.org/dc/elements/1.1/","dcterms":"http://purl.org/dc/terms/","foaf":"http://xmlns.com/foaf/0.1/","prism":"http://prismstandard.org/namespaces/basic/2.0/","cinii":"http://ci.nii.ac.jp/ns/1.0/","datacite":"https://schema.datacite.org/meta/kernel-4/","ndl":"http://ndl.go.jp/dcndl/terms/","jpcoar":"https://github.com/JPCOAR/schema/blob/master/2.0/"},"@id":"https://cir.nii.ac.jp/crid/1363951795366241536.json","@type":"Article","productIdentifier":[{"identifier":{"@type":"DOI","@value":"10.1016/j.eswa.2016.10.015"}},{"identifier":{"@type":"URI","@value":"https://api.elsevier.com/content/article/PII:S0957417416305449?httpAccept=text/plain"}},{"identifier":{"@type":"URI","@value":"https://api.elsevier.com/content/article/PII:S0957417416305449?httpAccept=text/xml"}}],"dc:title":[{"@value":"Data mining methods for knowledge discovery in multi-objective optimization: Part A - Survey"}],"creator":[{"@id":"https://cir.nii.ac.jp/crid/1383951795366241408","@type":"Researcher","foaf:name":[{"@value":"Sunith Bandaru"}]},{"@id":"https://cir.nii.ac.jp/crid/1383951795366241537","@type":"Researcher","foaf:name":[{"@value":"Amos H.C. Ng"}]},{"@id":"https://cir.nii.ac.jp/crid/1383951795366241536","@type":"Researcher","foaf:name":[{"@value":"Kalyanmoy Deb"}]}],"publication":{"publicationIdentifier":[{"@type":"PISSN","@value":"09574174"}],"prism:publicationName":[{"@value":"Expert Systems with Applications"}],"dc:publisher":[{"@value":"Elsevier BV"}],"prism:publicationDate":"2017-03","prism:volume":"70","prism:startingPage":"139","prism:endingPage":"159"},"reviewed":"false","dc:rights":["https://www.elsevier.com/tdm/userlicense/1.0/"],"url":[{"@id":"https://api.elsevier.com/content/article/PII:S0957417416305449?httpAccept=text/plain"},{"@id":"https://api.elsevier.com/content/article/PII:S0957417416305449?httpAccept=text/xml"}],"createdAt":"2016-10-18","modifiedAt":"2024-06-20","relatedProduct":[{"@id":"https://cir.nii.ac.jp/crid/1360013168746288384","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Physical insights into multi-point global optimum design of scramjet intakes for ascent flight"}]},{"@id":"https://cir.nii.ac.jp/crid/1360306906082087424","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Sensitivity analysis for knowledge discovery in scramjet intake design optimization using deep-learning flowfield prediction"}]},{"@id":"https://cir.nii.ac.jp/crid/1360848657067667456","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Data mining based on clustering and association rule analysis for knowledge discovery in multiobjective topology optimization"}]},{"@id":"https://cir.nii.ac.jp/crid/1360865815505422208","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Multi-objective design space exploration using explainable surrogate models"}]},{"@id":"https://cir.nii.ac.jp/crid/1360869854352928512","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@value":"Optimization and data mining for shock-induced mixing enhancement inside scramjet using stochastic deep-learning flowfield prediction"}]},{"@id":"https://cir.nii.ac.jp/crid/1390865718381371520","@type":"Article","resourceType":"学術雑誌論文(journal article)","relationType":["isReferencedBy"],"jpcoar:relatedTitle":[{"@language":"en","@value":"Analytical Characterization and Multi-Objective Optimization of Scramjet Intake Performance"}]}],"dataSourceIdentifier":[{"@type":"CROSSREF","@value":"10.1016/j.eswa.2016.10.015"},{"@type":"CROSSREF","@value":"10.1016/j.actaastro.2022.01.036_references_DOI_TVEuEGuetwNynPQZV4bNAiMHVea"},{"@type":"CROSSREF","@value":"10.2322/tjsass.68.57_references_DOI_TVEuEGuetwNynPQZV4bNAiMHVea"},{"@type":"CROSSREF","@value":"10.1016/j.ast.2024.109183_references_DOI_TVEuEGuetwNynPQZV4bNAiMHVea"},{"@type":"CROSSREF","@value":"10.1016/j.eswa.2018.10.047_references_DOI_TVEuEGuetwNynPQZV4bNAiMHVea"},{"@type":"CROSSREF","@value":"10.1007/s00158-024-03769-z_references_DOI_TVEuEGuetwNynPQZV4bNAiMHVea"},{"@type":"CROSSREF","@value":"10.1016/j.ast.2024.109513_references_DOI_TVEuEGuetwNynPQZV4bNAiMHVea"}]}