Searched for: subject%3A%22robustness%22
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van der Weide, Tim (author), Deng, Q. (author), Santos, Bruno F. (author)
Long-term heavy maintenance check schedules are crucial in the aviation industry since airlines need them to prepare the required maintenance tools, workforce, and aircraft spare parts. However, most airlines adopt a manual approach to plan the heavy maintenance check schedules in current practice. This manual process relies on the experience of...
journal article 2021
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Scheepmaker, G.M. (author), Goverde, R.M.P. (author)
Energy-efficient train driving is an important topic to railway undertakings (RUs) for sustainability and cost reduction. The timetable affects the possibilities for energy-efficient train driving by the amount of running time supplements, which is the topic of energy-efficient train timetabling (EETT). The scientific literature on EETT...
journal article 2021
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Vert, M.P.J. (author), Sharpanskykh, Alexei (author), Curran, R. (author)
Resilience is commonly understood as the capacity for a system to maintain a desirable state while undergoing adversity or to return to a desirable state as quickly as possible after being impacted. In this paper, we focus on resilience for complex sociotechnical systems (STS), specifically those where safety is an important aspect. Two main...
journal article 2021
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Zhang, Rongkai (author), Zhu, Jiang (author), Zha, Zhiyuan (author), Dauwels, J.H.G. (author), Wen, Bihan (author)
State-of-the-art image denoisers exploit various types of deep neural networks via deterministic training. Alternatively, very recent works utilize deep reinforcement learning for restoring images with diverse or unknown corruptions. Though deep reinforcement learning can generate effective policy networks for operator selection or architecture...
conference paper 2021
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Du, Zhe (author), Negenborn, R.R. (author), Reppa, V. (author)
Among the promising application of autonomous surface vessels (ASVs) is the utilization of multiple autonomous tugs for manipulating a floating object such as an oil platform, a broken ship, or a ship in port areas. Considering the real conditions and operations of maritime practice, this paper proposes a multi-agent control algorithm to...
journal article 2021
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He, Z. (author), Navneet, Kumar (author), van Dam, Wirdmer (author), Van Mieghem, P.F.A. (author)
Multimodal freight transport allows switching among different modes of transport to utilize transport facilities more efficiently. This paper proposes an approach on network modeling and robustness assessment for multimodal freight transport networks, where the nodes represent junctions, terminals and crossings, and the links represent...
journal article 2021
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Roy, S. (author), Lee, Jinoh (author), Baldi, S. (author)
This brief proposes a new adaptive-robust formulation for time-delay control (TDC) under a less-restrictive stability condition. TDC relies on estimating the unknown system dynamics via the artificial introduction of a time delay, often referred to as time-delay estimation (TDE). In conventional TDC, the estimation error, called TDE error, is...
journal article 2021
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van Parys, Bart P.G. (author), Mohajerin Esfahani, P. (author), Kuhn, Daniel (author)
We study stochastic programs where the decision maker cannot observe the distribution of the exogenous uncertainties but has access to a finite set of independent samples from this distribution. In this setting, the goal is to find a procedure that transforms the data to an estimate of the expected cost function under the unknown data...
journal article 2021
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Shavazipour, Babooshka (author), Kwakkel, J.H. (author), Miettinen, Kaisa (author)
This paper proposes a novel optimization approach for multi-scenario multi-objective robust decision making, as well as an alternative way for scenario discovery and identifying vulnerable scenarios even before any solution generation. To demonstrate and test the novel approach, we use the classic shallow lake problem. We compare the results...
journal article 2021
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Gravell, Benjamin (author), Mohajerin Esfahani, P. (author), Summers, Tyler H. (author)
The linear quadratic regulator (LQR) problem has reemerged as an important theoretical benchmark for reinforcement learning-based control of complex dynamical systems with continuous state and action spaces. In contrast with nearly all recent work in this area, we consider multiplicative noise models, which are increasingly relevant because...
journal article 2021
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Dhiman, Ashish (author), Sun, P. (author), Kooij, Robert (author)
This paper presents machine learning based approximations for the minimum number of driver nodes needed for structural controllability of networks under link-based random and targeted attacks. We compare our approximations with existing analytical approximations and show that our machine learning based approximations significantly outperform...
conference paper 2021
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Sun, P. (author), He, Z. (author), Kooij, Robert (author), Van Mieghem, P.F.A. (author)
Optical networks are vulnerable to failures due to targeted attacks or large-scale disasters. The recoverability of optical networks refers to the ability of an optical network to return to a desired performance level after suffering topological perturbations such as link failures. This paper proposes a general topological approach and...
journal article 2021
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L’Ortye, J. (author), Mitici, M.A. (author), Visser, H.G. (author)
At the interface between airport airside and landside operations, the assignment of flights to gates is key to ensure efficient operations and a high quality of service for passengers. We propose a mixed-integer linear program for an integrated flight-to-gate assignment that considers both airside as well as landside constraints on the...
journal article 2021
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Zuo, Renwei (author), Lv, Maolong (author), Li, Yinghui (author), Nie, Hongyan (author)
This paper presents an adaptive neural control to solve the tracking problem of a class of pure-feedback systems with non-differentiable non-affine functions in the presence of unknown periodically time-varying disturbances. To handle with the design difficulty from non-affine structure of pure-feedback system, a continuous and positive...
journal article 2021
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Sun, P. (author), Kooij, Robert (author), Van Mieghem, P.F.A. (author)
In this paper, we propose closed-form analytic approximations for the number of controllable nodes in sparse communication networks from the aspect of network controllability, considering link-based random attack, targeted attack, as well as random attack under the protection of critical links. We compare our approximations with simulation...
journal article 2021
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Kouw, W.M. (author), Loog, M. (author)
Consider a domain-adaptive supervised learning setting, where a classifier learns from labeled data in a source domain and unlabeled data in a target domain to predict the corresponding target labels. If the classifier’s assumption on the relationship between domains (e.g. covariate shift, common subspace, etc.) is valid, then it will usually...
journal article 2021
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Devia Pinzon, C.A. (author), Giordano, G. (author)
We study dynamic networks described by a directed graph where the nodes are associated with MIMO systems with transfer-function matrix F(s), representing individual dynamic units, and the arcs are associated with MIMO systems with transfer-function matrix G(s), accounting for the dynamic interactions among the units. In the nominal case, we...
journal article 2021
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Gravell, Benjamin J. (author), Mohajerin Esfahani, P. (author), Summers, Tyler H. (author)
Robust stability and stochastic stability have separately seen intense study in control theory for many decades. In this work we establish relations between these properties for discrete-time systems and employ them for robust control design. Specifically, we examine a multiplicative noise framework which models the inherent uncertainty and...
journal article 2021
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Ghiassi, S. (author), Birke, Robert (author), Chen, Lydia Y. (author)
Big Data systems allow collecting massive datasets to feed the data hungry deep learning. Labelling these ever-bigger datasets is increasingly challenging and label errors affect even highly curated sets. This makes robustness to label noise a critical property for weakly-supervised classifiers. The related works on resilient deep networks...
conference paper 2021
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Cañizares Gaztelu, J.C. (author), Copeland, S.M. (author), Doorn, N. (author)
While resilience is a major concept in development, climate adaptation, and related do-mains, many doubts remain about how to interpret this term, its relationship with closely overlap-ping terms, or its normativity. One major view is that, while resilience originally was a descriptive concept denoting some adaptive property of ecosystems,...
journal article 2021
Searched for: subject%3A%22robustness%22
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