지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 발행연도
- 2013.5
- 수록면
- 391 - 399 (9page)
이용수
이 논문의 연구 히스토리 (2)
2013
Development of a New Estimation and method using Neural Network for Robust Design Modeling and Optimization
Thanh-T
,
a Hoang
,
Tuan-Ho Le
외 1명
한국경영과학회 학술대회논문집
2013.05
학술대회자료
Development of a New Estimation and method using Neural Network for Robust Design Modeling and Optimization
Thanh-T
,
a Hoang
,
Tuan-Ho Le
외 1명
대한산업공학회 춘계공동학술대회 논문집
2013.05
학술대회자료
- 이 논문의 후속연구가 궁금하신가요?
- 연관 학술논문 또는 학술발표를 통해 보다 발전된 연구결과를 확인하실 수 있습니다.
- 이 논문의 연구 히스토리 확인하기
초록· 키워드
오류제보하기
Robust design (RD) is has emerged a key concept to achieve the consistentimprove product/process performance in an early design stage. It has also been recognized as cost effective methodology in market place for more than twenty years. Many RD methods including experimental design, estimation, and optimization, were reported in literature. However, there is room for improvement, products and processes which has significantly meaning in competitive manufacturing nowadays. Traditional The primary objective of this paper is to propose a new estimation method using neural network (NN) in order to provide an alternative aspect of response surface methodology (RSM) based on ordinary least squares method (LSM). Next, a new modeling by using NN approaches is then proposed in order to estimate a functional relationship between input factors and output responses.
Finally，a comparative study using simulation is performed as verification purposes. This simulation study demonstrates that the proposed NN-based RD method provides better optimal solutions than RSM.
Finally，a comparative study using simulation is performed as verification purposes. This simulation study demonstrates that the proposed NN-based RD method provides better optimal solutions than RSM.
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UCI(KEPA) : I410-ECN-0101-2018-020-000840954