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Machine Learning for Nonlinear Materials Characterization and Modeling
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Machine Learning for Nonlinear Materials Characterization and Modeling. |
| 개인저자 | Shea, Daniel e. |
| 단체저자명 | University of Washington. Materials Science and Engineering. |
| 발행사항 | [S.l.]: University of Washington., 2021. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2021. |
| 형태사항 | 130 p. |
| 기본자료 저록 | Dissertations Abstracts International 83-02B. Dissertation Abstract International |
| ISBN | 9798535507170 |
| 학위논문주기 | Thesis (Ph.D.)--University of Washington, 2021. |
| 일반주기 |
Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
Advisor: Kutz, J. Nathan;Brunton, Steven L. |
| 이용제한사항 | This item must not be sold to any third party vendors. |
| 일반주제명 | Computational physics. Applied mathematics. Materials science. Deep learning. Datasets. Collaboration. Identification. Dissertations & theses. Eigen values. Decomposition. Noise. Physical sciences. Time series. Dynamical systems. 20th century. Boundary value problems. Heat transfer. Quantum physics. Partial differential equations. Coordinate transformations. Oscillators. Engineering. Algorithms. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
