Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

RSPSO(Residual weighted Sparse Particle Swarm Optimization)를 활용한 고차원 오버레이 샘플링 선정기법

Full metadata record
DC Field Value Language
dc.contributor.authorJun-Geol Baek-
dc.date.accessioned2021-08-27T13:35:54Z-
dc.date.available2021-08-27T13:35:54Z-
dc.date.created2021-04-22-
dc.date.issued2019-11-08-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/8469-
dc.publisher대한산업공학회-
dc.titleRSPSO(Residual weighted Sparse Particle Swarm Optimization)를 활용한 고차원 오버레이 샘플링 선정기법-
dc.title.alternativeRSPSO(Residual weighted Sparse Particle Swarm Optimization)를 활용한 고차원 오버레이 샘플링 선정기법-
dc.typeConference-
dc.contributor.affiliatedAuthorJun-Geol Baek-
dc.identifier.bibliographicCitation2019 대한산업공학회 추계학술대회-
dc.relation.isPartOf2019 대한산업공학회 추계학술대회-
dc.relation.isPartOf2019 대한산업공학회 추계학술대회 논문집-
dc.citation.title2019 대한산업공학회 추계학술대회-
dc.citation.conferencePlaceKO-
dc.citation.conferencePlace서울(서울대학교)-
dc.citation.conferenceDate2019-11-08-
dc.type.rimsCONF-
dc.description.journalClass2-
Files in This Item
There are no files associated with this item.
Appears in
Collections
College of Engineering > School of Industrial and Management Engineering > 2. Conference Papers

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Baek, Jun Geol photo

Baek, Jun Geol
공과대학 (산업경영공학부)
Read more

Altmetrics

Total Views & Downloads

BROWSE