Results 81 to 90 of about 8,860,352 (207)
An integrated energy system (IES) coupled with hydrogen energy is significantly influenced by source-load uncertainties when operating alone. Traditional robust optimization techniques are overly conservative, which impedes the economic performance.
Xiaoqiang DING, Zhi YUAN, Ji LI
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Consensus Decision Modeling with Distributionally Robust Chance Constraint in Uncertain Environments
Group decision-making (GDM) in an ambiguous environment has consistently become a research focus in the decision science field during the past decade. Existing minimum cost consensus models either control the total budget in a deterministic context or ...
Dai Zexing +3 more
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Distributionally Robust Observable Strategic Queues
This paper presents an extension of Naor’s analysis on the join-or-balk problem in observable M/M/1 queues. Although all other Markovian assumptions still hold, we explore this problem assuming uncertain arrival rates under the distributionally robust settings. We first study the problem with the classical moment ambiguity set, where the support, mean,
Yijie Wang +3 more
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Natural disasters would destroy power grids and lead to blackouts. To enhance resilience of distribution systems, the sequential load restoration strategy can be adopted to restore outage portions using a sequence of control actions, such as switch on ...
Yangwu Shen +5 more
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Distributionally robust Lyapunov–Barrier Networks for safe and stable control under uncertainty
This paper addresses the challenge of simultaneously achieving stability and safety in nonlinear control systems subject to uncertain parameters. We propose distributionally robust Lyapunov–Barrier networks (DR-LBNs), a novel framework that unifies ...
Ali Baheri
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Flow-Based Distributionally Robust Optimization
IEEE Journal on Selected Areas in Information Theory (JSAIT).
Chen Xu +3 more
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Distributionally Robust Policy and Lyapunov-Certificate Learning
This article presents novel methods for synthesizing distributionally robust stabilizing neural controllers and certificates for control systems under model uncertainty.
Kehan Long +2 more
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Distributionally Robust Optimization with Polynomial Robust Constraints
25 ...
Jiawang Nie, Suhan Zhong
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A new distributionally robust reward-risk model for portfolio optimization
A new distributionally robust ratio optimization model is proposed under the known first and second moments of the uncertain distributions. In this article, both standard deviation (SD) and conditional value-at-risk (CVaR) are used to measure the risk ...
Zhou Yijia, Xu Lijun
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Distributionally Robust Recourse Action
A recourse action aims to explain a particular algorithmic decision by showing one specific way in which the instance could be modified to receive an alternate outcome. Existing recourse generation methods often assume that the machine learning model does not change over time.
Nguyen, Duy, Bui, Ngoc, Nguyen, Viet Anh
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