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Strategic Monte Carlo and Variational Methods in Statistical Data Assimilation for Nonlinear Dynamical Systems
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| 자료유형 | E-Book |
|---|---|
| 개인저자 | Shirman, Aleksandra. |
| 단체저자명 | University of California, San Diego. Physics. |
| 서명/저자사항 | Strategic Monte Carlo and Variational Methods in Statistical Data Assimilation for Nonlinear Dynamical Systems. |
| 발행사항 | [S.l.] : University of California, San Diego., 2018 |
| 발행사항 | Ann Arbor : ProQuest Dissertations & Theses, 2018 |
| 형태사항 | 102 p. |
| 소장본 주기 | School code: 0033. |
| ISBN | 9780438088764 |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
Adviser: Henry D. I. Abarbanel. |
| 요약 | Data Assimilation (DA) is a method through which information is extracted from measured quantities and with the help of a mathematical model is transferred through a probability distribution to unknown or unmeasured states and parameters charact |
| 요약 | Many recent DA efforts rely on an probability distribution optimization that locates the most probable state and parameter values given a set of data. The procedure developed and demonstrated here extends the optimization by appending a biased r |
| 요약 | This thesis will conclude with an exploration of the equivalence of machine learning and the formulation of statistical DA. The application of previous DA methods are demonstrated on the classic machine learning problem: the characterization of |
| 일반주제명 | Physics. Statistics. Biophysics. |
| 언어 | 영어 |
| 기본자료 저록 | Dissertation Abstracts International79-11B(E). Dissertation Abstract International |
| 대출바로가기 | http://www.riss.kr/pdu/ddodLink.do?id=T14998740 |
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| No. | 등록번호 | 청구기호 | 소장처 | 도서상태 | 반납예정일 | 예약 | 서비스 | 매체정보 |
|---|---|---|---|---|---|---|---|---|
| 1 | WE00028111 | 530 | 가야대학교/전자책서버(컴퓨터서버)/ | 대출가능 |
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