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Methods for Scientific Simulation, Machine Learning, and Nonlinear Control
Methods for Scientific Simulation, Machine Learning, and Nonlinear Control
Detailed Information
- Material Type
- 단행본
- ISBN
- 9798534673630
- DDC
- 519
- Author
- Boffi, Nicholas M.
- Title/Author
- Methods for Scientific Simulation, Machine Learning, and Nonlinear Control
- Publish Info
- [Sl] : Harvard University, 2021
- Publish Info
- Ann Arbor : ProQuest Dissertations & Theses, 2021
- Material Info
- 315 p
- General Note
- Source: Dissertations Abstracts International, Volume: 83-02, Section: B.
- General Note
- Advisor: Rycroft, C.;Slotine, J.
- 학위논문주기
- Thesis (Ph.D.)--Harvard University, 2021.
- Restrictions on Access Note
- This item must not be sold to any third party vendors.
- Subject Added Entry-Topical Term
- Applied mathematics
- Subject Added Entry-Topical Term
- Engineering
- Subject Added Entry-Topical Term
- Systems science
- Subject Added Entry-Topical Term
- Simulation
- Subject Added Entry-Topical Term
- Velocity
- Subject Added Entry-Topical Term
- Experiments
- Subject Added Entry-Topical Term
- Generalized linear models
- Subject Added Entry-Topical Term
- Optimization
- Subject Added Entry-Topical Term
- Adaptation
- Subject Added Entry-Topical Term
- Algorithms
- Subject Added Entry-Topical Term
- Boundary conditions
- Subject Added Entry-Topical Term
- Friction welding
- Index Term-Uncontrolled
- Computational mathematics
- Index Term-Uncontrolled
- Control theory
- Index Term-Uncontrolled
- Dynamical systems
- Index Term-Uncontrolled
- Machine learning
- Index Term-Uncontrolled
- Optimization
- Index Term-Uncontrolled
- Scientific computing
- Added Entry-Corporate Name
- Harvard University Engineering and Applied Sciences - Applied Math
- Host Item Entry
- Dissertations Abstracts International. 83-02B.
- Host Item Entry
- Dissertation Abstract International
- Electronic Location and Access
- 로그인 후 원문을 볼 수 있습니다.
- 소장사항
-
202202 2022
MARC
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■035 ▼a(MiAaPQ)AAI28499365
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a519
■1001 ▼aBoffi, Nicholas M.▼0(orcid)0000-0003-1336-7568
■24510▼aMethods for Scientific Simulation, Machine Learning, and Nonlinear Control
■260 ▼a[Sl]▼bHarvard University▼c2021
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2021
■300 ▼a315 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 83-02, Section: B.
■500 ▼aAdvisor: Rycroft, C.;Slotine, J.
■5021 ▼aThesis (Ph.D.)--Harvard University, 2021.
■506 ▼aThis item must not be sold to any third party vendors.
■590 ▼aSchool code: 0084.
■650 4▼aApplied mathematics
■650 4▼aEngineering
■650 4▼aSystems science
■650 4▼aSimulation
■650 4▼aVelocity
■650 4▼aExperiments
■650 4▼aGeneralized linear models
■650 4▼aOptimization
■650 4▼aAdaptation
■650 4▼aAlgorithms
■650 4▼aBoundary conditions
■650 4▼aFriction welding
■653 ▼aComputational mathematics
■653 ▼aControl theory
■653 ▼aDynamical systems
■653 ▼aMachine learning
■653 ▼aOptimization
■653 ▼aScientific computing
■690 ▼a0364
■690 ▼a0537
■690 ▼a0790
■71020▼aHarvard University▼bEngineering and Applied Sciences - Applied Math.
■7730 ▼tDissertations Abstracts International▼g83-02B.
■773 ▼tDissertation Abstract International
■790 ▼a0084
■791 ▼aPh.D.
■792 ▼a2021
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T16052223▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
■980 ▼a202202▼f2022
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