상세정보
Export to Refworks부가기능
On Particle Methods for Uncertainty Quantification in Complex Systems
상세 프로파일
| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | On Particle Methods for Uncertainty Quantification in Complex Systems. |
| 개인저자 | Yang, Chao. |
| 단체저자명 | The Ohio State University. Mechanical Engineering. |
| 발행사항 | [S.l.]: The Ohio State University., 2017. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2017. |
| 형태사항 | 221 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
| ISBN | 9780438098268 |
| 학위논문주기 | Thesis (Ph.D.)--The Ohio State University, 2017. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Mrinal Kumar. |
| 요약 | This dissertation aims to study three crucial problems related to Monte Carlo based particle methods for solving uncertainty quantification problems in complex systems. The first problem concerns the existence of a "benchmark" sampling method th |
| 요약 | Inspired by the new MCMC-MOC approach, a second problem on the transient effectiveness of MCS is posed in the context of Markov chain Monte Carlo theory. The propagated ensemble is viewed as the realization of a Markov chain at each time instant |
| 요약 | The third and final problem addressed in this dissertation is the following: "is it possible to develop adaptation rules for MCS such that it may perform within prescribed bounds of accuracy using the "minimum" possible number of simulations at |
| 일반주제명 | Mechanical engineering. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
