DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Chang, Daejun | - |
dc.contributor.advisor | 장대준 | - |
dc.contributor.author | Yoo, Seunghyeon | - |
dc.date.accessioned | 2023-06-23T19:35:12Z | - |
dc.date.available | 2023-06-23T19:35:12Z | - |
dc.date.issued | 2022 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1007765&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/309364 | - |
dc.description | 학위논문(박사) - 한국과학기술원 : 해양시스템대학원, 2022.8,[XVIII, 111 p. :] | - |
dc.description.abstract | In this study, a black-box time-continuous simulation model verification framework was developed based on Gaussian process regression (GPR), which is a method of adaptive input space searching regardless of the first-principles equations behind a subject simulation model. Further, pre-developed simulation model verification methodologies and their applicability to a time-continuous black-box simulation model were investigated. An aggregated GPR model was utilised for the adaptive input space search algorithm, serving as a key sub-process of the simulation model verification framework. Finally, a case study was performed by employing the proposed framework to verify a hybrid marine propulsion system consisting of heterogeneously generated time-continuous simulation models. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Gaussian process regression▼asimulation model verification▼amarine hybrid propulsion system▼aco-simulation | - |
dc.subject | 가우시안 프로세스 회귀분석▼a시뮬레이션 모델 검증▼a복합 선박 추진 시스템▼a통합시뮬레이션 | - |
dc.title | Verification framework for continuous-time black-box models based on Gaussian process regression applied to co-simulation of marine propulsion system | - |
dc.title.alternative | 가우시안 프로세스 회귀법에 기반한 선박 추진 용 연속시간 블랙박스 모델 검증 방법론에 관한 연구 | - |
dc.type | Thesis(Ph.D) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :해양시스템대학원, | - |
dc.contributor.alternativeauthor | 유승현 | - |
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