Searched for: subject%3A%22Artificial%255C+neural%255C+networks%22
(41 - 60 of 114)
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Liu, S. (author), Grzelak, L.A. (author), Oosterlee, C.W. (author)We propose an accurate data-driven numerical scheme to solve stochastic differential equations (SDEs), by taking large time steps. The SDE discretization is built up by means of the polynomial chaos expansion method, on the basis of accurately determined stochastic collocation (SC) points. By employing an artificial neural network to learn these...journal article 2022
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Jeken Rico, P. (author)The following project deals with the optimization of simulation parameters such as the injection location and pitch angle of polyurethane foaming simulations using artificial neural networks. The model's target is to predict quality variables based on the process parameters and the geometry features. Through several evaluations of the model,...master thesis 2021
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Verma, Ayush (author)With growing wind energy capacity, especially offshore, reliability of wind turbines (WT) becomes a relevant concern. Poor reliability directly affects their cost effectiveness due to increased operation and maintenance ...master thesis 2021
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Cuperman Coifman, Rafael (author)been given to Human Activity Recognition (HAR) based on signals obtained by IMUs placed on different body parts. This thesis studies the usage of Deep Learning-based models to recognize different football activities in an accurate, robust, and fast manner. Several deep architectures were trained with data captured with IMU sensors placed on...master thesis 2021
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Van Santvliet, Pieter (author), Rozendaal, Aart (author)This thesis shows the detailed design of the control and software of a DC microgrid of a tiny house community on the roof of a high-rise building in the city of Rotterdam in the Netherlands, consisting of twelve tiny houses powered by solar and wind energy. This thesis is part of a project with two other subgroups, focusing on the microgrid...bachelor thesis 2021
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Saz Ulibarrena, Veronica (author)The use of low-thrust propulsion for interplanetary missions requires the implementation of new methods for the preliminary design of their trajectories. This thesis proposes a method using the Monotonic Basin Hopping global optimization algorithm to find feasible trajectories with optimum use of the mass of fuel for the case in which the...master thesis 2021
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van der Woude, Mark (author)Widespread usage of Micro Aerial Vehicles (MAVs) has led to various airspace safety breaches, including near mid-air collisions with other aircraft. To ensure safe integration into general aviation, it is paramount that MAVs are equipped with an autonomous detect and avoid system when flying beyond the visual line-of-sight of the operator. The...master thesis 2021
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van den Haak, Daniel (author)Lane change decision-making is an important challenge for automated vehicles, urging the need for high performance algorithms that are able to handle complex traffic situations. Deep reinforcement learning (DRL), a machine learning method based on artificial neural networks, has recently become a popular choice for modelling the lane change...master thesis 2021
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Becker, Midas (author)<br/>Being a safe and healthy alternative for polluting and space-inefficient motorised vehicles, cycling can strongly improve living conditions in urban areas. Idling in front of traffic lights is seen as one of the major inconveniences of commuting by bicycle. By giving personalised speed advice, the probability of catching a green light can...master thesis 2021
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Brederveld, Jan (author)Various machine learning algorithms have been applied to find optimal lowthrust<br/>satellite trajectories, however, no fair comparison of their accuracy has been made yet. In this paper, two common and promising supervised machine learning algorithms are compared for their regression capacities:<br/>the artificial neural network and the...master thesis 2021
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Tsekos, C. (author), Tandurella, S. (author), de Jong, W. (author)As the push towards more sustainable ways to produce energy and chemicals intensifies, efforts are needed to refine and optimize the systems that can give an answer to these needs. In the present work, the use of neural networks as modelling tools for lignocellulosic biomass pyrolysis main products yields estimation was evaluated. In order to...journal article 2021
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Sun, B. (author), van Kampen, E. (author)The scarcity of information regarding dynamics and full-state feedback increases the demand for a model-free control technique that can cope with partial observability. To deal with the absence of prior knowledge of system dynamics and perfect measurements, this paper develops a novel intelligent control scheme by combining global dual...journal article 2021
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Cheng, L. (author), Xin, H. (author), Groves, R.M. (author), Veljkovic, M. (author)Acoustic emission (AE) is often used for structural health monitoring (SHM) in the wide field of engineering structures and one of its most beneficial attributes is the ability to localize the damage/crack based on the AE events. The vast majority of ongoing work on AE monitoring focues on geometrically simple structures or a confined area,...journal article 2021
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Imani, Maryam (author), Hasan, Md Mahmudul (author), Bittencourt, Luiz Fernando (author), McClymont, Kent (author), Kapelan, Z. (author)Resilience-informed water quality management embraces the growing environmental challenges and provides greater accuracy by unpacking the systems' characteristics in response to failure conditions in order to identify more effective opportunities for intervention. Assessing the resilience of water quality requires complex analysis of...journal article 2021
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Salvador, Beatriz (author), Oosterlee, C.W. (author), van der Meer, R. (author)Artificial neural networks (ANNs) have recently also been applied to solve partial differential equations (PDEs). The classical problem of pricing European and American financial options, based on the corresponding PDE formulations, is studied here. Instead of using numerical techniques based on finite element or difference methods, we...journal article 2021
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Cao, Yixing (author), Chen, Shanghuan (author), Li, Yutong (author), Du, Yunjia (author), Chen, Wei (author), Fan, J. (author), Zhang, Kouchi (author)The emission spectra of high color rendering phosphors, mixed with the yttrium aluminium garnet, silicon based oxynitride and nitride based phosphors, were predicted by the Lambert-Beer theory and back propagation neural network (BP NN). Firstly, the modified Lambert-Beer model was used to calculate the proportional coefficient of the...journal article 2021
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Antonopoulos, Ioannis (author), Robu, Valentin (author), Couraud, Benoit (author), Flynn, David (author)Recent years have seen an increasing interest in Demand Response (DR), as a means to satisfy the growing flexibility needs of modern power grids. This increased flexibility is required due to the growing proportion of intermittent renewable energy generation into the energy mix, and increasing complexity in demand profiles from the...journal article 2021
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Alwosheel, A.S.A. (author), van Cranenburgh, S. (author), Chorus, C.G. (author)Artificial Neural Networks (ANNs) are rapidly gaining popularity in transportation research in general and travel demand analysis in particular. While ANNs typically outperform conventional methods in terms of predictive performance, they suffer from limited explainability. That is, it is very difficult to assess whether or not particular...journal article 2021
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Rosin, T. R. (author), Romano, M. (author), Keedwell, E. (author), Kapelan, Z. (author)Combined Sewer Overflows (CSOs) are a major source of pollution and urban flooding, spilling untreated wastewater directly into water bodies and the surrounding environment. If overflows can be predicted sufficiently in advance, then techniques are available for mitigation. This paper presents a novel bi-model committee evolutionary...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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