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Goldman, Thomas (author)This thesis proposes an unsupervised Physics-Informed Neural Network (PINN) for solving optimal control problems with the direct method to design and optimize transfer trajectories. The network adheres analytically to boundary conditions and includes the objective fitness as regularization in its loss function. A test scenario of a planar Earth...master thesis 2023
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Liu, Chengen (author), Leus, G.J.T. (author), Isufi, E. (author)The edge flow reconstruction task consists of retreiving edge flow signals from corrupted or incomplete measurements. This is typically solved by a regularized optimization problem on higher-order networks such as simplicial complexes and the corresponding regularizers are chosen based on prior knowledge. Tailoring this prior to the setting...journal article 2023
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Rizki, Z. (author), Ottens, M. (author)Membrane technology is commonly used within food, bio- and pharmaceutical processes. Beside single-stage membranes, multi-stage membrane systems are become more popular to improve separation performance. In this review, we present a unified four-phase model-based optimization framework to optimize these systems, using mechanistic models,...review 2023
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Mc Donald, Tom (author)Recently, ReLU neural networks have been modelled as constraints in mixed integer linear programming (MILP) enabling surrogate-based optimisation in various domains as well as efficient solution of machine learning verification problems. However, previous works have been limited to multilayer perceptrons (MLPs). The Graph Convolutional Neural...master thesis 2022
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Everingham, Dylan (author)The development of optical metamaterials in recent years has enabled the design of novel optical devices with exciting properties and applications ranging across many fields, including in scientific instrumentation for space missions. This in<br/>turn has led to demand for computational methods which can produce efficient device designs....master thesis 2022
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Stoel, Fianne (author)District heating systems (DHSs) have the potential to play a big part in the energy transition. The efficient operation of DHSs is therefore also an important subject of study. The operation of DHSs where combined heat and power (CHP) plants are used are particularly interesting, because CHPs can operate with high efficiency.<br/><br/>In this...master thesis 2022
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van Bokkem, Dirk (author)The increasing global food demand, accompanied by the decreasing number of expert growers, brings the need for more sustainable and efficient solutions in horticulture. Consultancy company Delphy aims to face this challenge by taking a more data-driven approach, by means of autonomous growing inside the greenhouse. The controlled environment of...master thesis 2022
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Mkhoyan, T. (author), Ruland, O.L. (author), De Breuker, R. (author), Wang, Xuerui (author)Inspired by nature, smart morphing technologies enable the aircraft of tomorrow to sense their environment and adapt the shape of their wings in flight to minimize fuel consumption and emissions. A primary challenge on the road to this feature is how to use the knowledge gathered from sensory data to establish an optimal shape adaptively and...journal article 2022
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Kon, Johan (author), Bruijnen, Dennis (author), van de Wijdeven, Jeroen (author), Heertjes, Marcel (author), Oomen, T.A.E. (author)Unknown nonlinear dynamics often limit the tracking performance of feedforward control. The aim of this paper is to develop a feedforward control framework that can compensate these unknown nonlinear dynamics using universal function approximators. The feedforward controller is parametrized as a parallel combination of a physics-based model and...conference paper 2022
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Suryanarayanan, Surya Narayanan (author)Inverse design with topology optimization has followed the same computational<br/>graph for decades. The unknown material density is distributed within a domain,<br/>a computational analysis predicts the response of that design and its derivative<br/>with respect to the unknown, and this information is used by a chosen gradient<br/>based...master thesis 2021
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Qian, Yichen (author), Hou, F. (author), Fan, J. (author), Lv, Quanya (author), Fan, X. (author), Zhang, Kouchi (author)A new panel-level silicon carbide (SiC) metal oxide semiconductor field effect transistor (MOSFET) power module was developed by using the fan-out and embedded chip technologies. To achieve the more effective thermal management and higher reliability under thermal cycling, a new optimization method called Ant colony optimization-back...journal article 2021
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Nguyen, Hoa Minh (author), Rueda, José L. (author), Lekić, A. (author), Pham, Hoan Van (author)The paper presents an approach for online centralized control in active distribution networks. It combines a proportional integral (PI) control unit with a corrective control unit (CCU), based on the principle of Model Predictive Control (MPC). The proposed controller is designed to accommodate the increasing penetration of distributed...journal article 2021
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den Ottelander, Tom (author)Computer vision tasks, like supervised image classification, are effectively tackled by convolutional neural networks, provided that the architecture, which defines the structure of the network, is set correctly. Neural Architecture Search (NAS) is a relatively young and increasingly popular field that is concerned with automatically optimizing...master thesis 2020
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Þorbjarnarson, T. (author)Recent work has shown potential in using Mixed Integer Programming (MIP) solvers to optimize certain aspects of neural networks (NN). However little research has gone into training NNs with MIP solvers. State of the art methods to train NNs are typically gradient-based and require significant amounts of data, computation on GPUs and extensive...master thesis 2020
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Pal, Somnath (author)The total electrical energy consumption by all the operational data centers (located all over the world) is enormous (approx. 1% of the global electricity demand 20000TWh). This electrical energy is required 24x7 to operate and cool all the IT equipment present in the data center. The electrical energy required to cool all...master thesis 2020
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Schönfeld, Mariette (author)Machine learning has been a computer sciences buzzword for years. The technology has a lot of potential and a huge number of applications that spoke to people with and without knowledge of computer sciences. Image, text and speech recognition, social profiling, computergames, everything seemed possible. Machine learning is not as much in the...bachelor thesis 2020
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de Bruin, T.D. (author), Kober, J. (author), Tuyls, Karl (author), Babuska, R. (author)Deep reinforcement learning makes it possible to train control policies that map high-dimensional observations to actions. These methods typically use gradient-based optimization techniques to enable relatively efficient learning, but are notoriously sensitive to hyperparameter choices and do not have good convergence properties. Gradient...journal article 2020
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Nakayama, S. (author), Blacquière, G. (author), Ishiyama, Tomohide (author)Blended acquisition along with efficient spatial sampling is capable of providing high-quality seismic data in a cost-effective and productive manner. While deblending and data reconstruction conventionally accompany this way of data acquisition, the recorded data can be processed directly to estimate subsurface properties. We establish a...journal article 2019
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Calli, B. (author), Caarls, W. (author), Wisse, M. (author), Jonker, P.P. (author)In this paper, a novel active vision strategy is proposed for optimizing the viewpoint of a robot's vision sensor for a given success criterion. The strategy is based on extremum seeking control (ESC), which introduces two main advantages: 1) Our approach is model free: It does not require an explicit objective function or any other task...journal article 2018