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Online Learning and Its Applications in Electricity Markets
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Online Learning and Its Applications in Electricity Markets. |
| 개인저자 | Baltaoglu, Mukadder Sevi. |
| 단체저자명 | Cornell University. Electrical & Computer Engineering. |
| 발행사항 | [S.l.]: Cornell University., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 127 p. |
| 기본자료 저록 | Dissertation Abstracts International 80-01B(E). Dissertation Abstract International |
| ISBN | 9780438343221 |
| 학위논문주기 | Thesis (Ph.D.)--Cornell University, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 80-01(E), Section: B.
Adviser: Lang Tong. |
| 요약 | Online learning is the process of learning to make accurate predictions and optimize actions sequentially in each period based on the information gained through the previous decisions and observations. In many real-world problems, the underlying |
| 요약 | We first study the problem of online learning and optimization of unknown Markov jump affine models which is motivated by the dynamic pricing problem of an electricity retailer. An online learning policy, referred to as Markovian simultaneous pe |
| 요약 | Motivated by virtual trading in two-settlement wholesale electricity markets, the second problem we consider is the online learning problem of optimal bidding strategy in repeated multi-commodity auctions. A polynomial-time online learning algor |
| 일반주제명 | Electrical engineering. Artificial intelligence. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
