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Suryanarayana, Gowri (author), Lago, Jesus (author), Geysen, Davy (author), Aleksiejuk, Piotr (author), Johansson, Christian (author)Recent research has seen several forecasting methods being applied for heat load forecasting of district heating networks. This paper presents two methods that gain significant improvements compared to the previous works. First, an automated way of handling non-linear dependencies in linear models is presented. In this context, the paper...journal article 2018
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Lago, Jesus (author), De Brabandere, Karel (author), De Ridder, Fjo (author), De Schutter, B.H.K. (author)Due to the increasing integration of solar power into the electrical grid, forecasting short-term solar irradiance has become key for many applications, e.g. operational planning, power purchases, reserve activation, etc. In this context, as solar generators are geographically dispersed and ground measurements are not always easy to obtain,...journal article 2018
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Mozaffar, M. (author), Bostanabad, R. (author), Chen, W. (author), Ehmann, K. (author), Cao, J. (author), Bessa, M.A. (author)Plasticity theory aims at describing the yield loci and work hardening of a material under general deformation states. Most of its complexity arises from the nontrivial dependence of the yield loci on the complete strain history of a material and its microstructure. This motivated 3 ingenious simplifications that underpinned a century of...journal article 2019
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Ghavamian, F. (author), Simone, A. (author)FE<sup>2</sup> multiscale simulations of history-dependent materials are accelerated by means of a recurrent neural network (RNN) surrogate for the history-dependent micro level response. We propose a simple strategy to efficiently collect stress–strain data from the micro model, and we modify the RNN model such that it resembles a nonlinear...journal article 2019
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Castillo, Jose M.T. (author), Arif, Muhammad (author), Niessen, W.J. (author), Schoots, Ivo G. (author), Veenland, J.F. (author)Significant prostate carcinoma (sPCa) classification based on MRI using radiomics or deep learning approaches has gained much interest, due to the potential application in assisting in clinical decision-making. Objective: To systematically review the literature (i) to determine which algorithms are most frequently used for sPCa classification...journal article 2020
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Qu, Dingran (author), Qiao, Tiezhu (author), Pang, Y. (author), Yang, Yi (author), Zhang, Haitao (author)Belt conveyor is considered as a momentous component of modern coal mining transportation system, and thus it is an essential task to diagnose and monitor the damage of belt in real time and accurately. Based on the deep learning algorithm, this present study proposes a method of conveyor belt damage detection based on ADCN (Adaptive Deep...journal article 2021
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Schweidtmann, A.M. (author), Esche, Erik (author), Fischer, Asja (author), Kloft, Marius (author), Repke, Jens Uwe (author), Sager, Sebastian (author), Mitsos, Alexander (author)The transformation of the chemical industry to renewable energy and feedstock supply requires new paradigms for the design of flexible plants, (bio-)catalysts, and functional materials. Recent breakthroughs in machine learning (ML) provide unique opportunities, but only joint interdisciplinary research between the ML and chemical engineering ...review 2021
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Lago, Jesus (author), Marcjasz, Grzegorz (author), De Schutter, B.H.K. (author), Weron, Rafał (author)While the field of electricity price forecasting has benefited from plenty of contributions in the last two decades, it arguably lacks a rigorous approach to evaluating new predictive algorithms. The latter are often compared using unique, not publicly available datasets and across too short and limited to one market test samples. The...review 2021
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Smirnova, Alisa (author), Yang, J. (author), Yang, Dingqi (author), Cudre-Mauroux, Philippe (author)Noisy labels represent one of the key issues in supervised machine learning. Existing work for label noise reduction mainly takes a probabilistic approach that infers true labels from data distributions in low-level feature spaces. Such an approach is not only limited by its capability to learn high-quality data representations, but also by...journal article 2022
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Mostafavi, F. (author), Tahsildoost, Mohammad (author), Zomorodian, Zahra Sadat (author), Shahrestani, Seyed Shayan (author)Purpose: In this study, a novel framework based on deep learning models is presented to assess energy and environmental performance of a given building space layout, facilitating the decision-making process at the early-stage design. Design/methodology/approach: A methodology using an image-based deep learning model called pix2pix is proposed...journal article 2022
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Castillo, J.M. (author), Arif, M. (author), Starmans, M.P.A. (author), Niessen, W.J. (author), Bangma, C.H. (author), Schoots, Ivo G. (author), Veenland, J.F. (author)The computer-aided analysis of prostate multiparametric MRI (mpMRI) could improve significant-prostate-cancer (PCa) detection. Various deep-learning-and radiomics-based methods for significant-PCa segmentation or classification have been reported in the literature. To be able to assess the generalizability of the performance of these methods,...journal article 2022
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Wang, Dandan (author), Xu, Jinlan (author), Gao, Fei (author), Wang, C.C. (author), Gu, Renshu (author), Lin, Fei (author), Rabczuk, Timon (author), Xu, Gang (author)In this paper, a deep learning framework combined with isogeometric analysis (IGA for short) called IGA-Reuse-Net is proposed for efficient reuse of numerical simulation on a set of topology-consistent models. Compared with previous data-driven numerical simulation methods only for simple computational domains, our method can predict high...journal article 2022
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Merkx, D.G.M. (author), Scholten, Sebastiaan (author), Frank, Stefan L. (author), Ernestus, Mirjam (author), Scharenborg, O.E. (author)Many computational models of speech recognition assume that the set of target words is already given. This implies that these models learn to recognise speech in a biologically unrealistic manner, i.e. with prior lexical knowledge and explicit supervision. In contrast, visually grounded speech models learn to recognise speech without prior...journal article 2022
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Pérez-Dattari, Rodrigo (author), Ferreira de Brito, B.F. (author), de Groot, O.M. (author), Kober, J. (author), Alonso-Mora, J. (author)The successful integration of autonomous robots in real-world environments strongly depends on their ability to reason from context and take socially acceptable actions. Current autonomous navigation systems mainly rely on geometric information and hard-coded rules to induce safe and socially compliant behaviors. Yet, in unstructured urban...journal article 2022
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Xiao, C. (author), Lin, H.X. (author), Leeuwenburgh, O. (author), Heemink, A.W. (author)History matching can play a key role in improving geological characterization and reducing the uncertainty of reservoir model predictions. Application of reservoir history matching is restricted by the huge computational cost by amongst others the many runs of the full model. Surrogate models with a reduced complexity are therefore used to...journal article 2022
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Nastos Konstantopoulos, C. (author), Komninos, P. (author), Zarouchas, D. (author)A hybrid methodology based on numerical and non-destructive experimental schemes, which is able to predict the structural level strength of composite laminates is proposed on the current work. The main objective is to predict the strength by substituting the up to failure experiments with non-destructive experiments where the investigated...journal article 2023
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Song, Yang (author), Wang, H. (author), Frøseth, Gunnstein (author), Nåvik, Petter (author), Liu, Zhigang (author), Rønnquist, Anders (author)The interaction performance of the pantograph-catenary is of great importance as it directly determines the current collection quality and operational safety of trains. The finite element method (FEM) is dominantly used for simulating pantograph-catenary interaction, which is normally computationally heavy. In this work, addressing the...journal article 2023
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Abdellatif, Alaa Awad (author), Mhaisen, N. (author), Mohamed, Amr (author), Erbad, Aiman (author), Guizani, Mohsen (author)The rise of chronic disease patients and the pandemic pose immediate threats to healthcare expenditure and mortality rates. This calls for transforming healthcare systems away from one-on-one patient treatment into intelligent health systems, leveraging the recent advances of Internet of Things and smart sensors. Meanwhile, reinforcement...journal article 2023
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Yin, Xilin (author), Wang, H. (author), Pisano, F. (author), Gavin, Kenneth (author), Askarinejad, A. (author), Zhou, Hongpeng (author)Predicting the non-linear loading response is the key to the design of suction caissons. This paper presents a systematic study to explore the applicability of deep learning techniques in foundation design. Firstly, a series of three-dimensional finite element simulations was performed, covering a wide range of embedment ratios and different...journal article 2023
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do Lago, Cesar A.F. (author), Giacomoni, Marcio H. (author), Bentivoglio, Roberto (author), Taormina, R. (author), Gomes, Marcus N. (author), Mendiondo, Eduardo M. (author)Two-dimensional hydrodynamic models are computationally expensive. This drawback can limit their application to solving problems requiring real-time predictions or several simulation runs. Although the literature presented improvements in using Deep Learning as an alternative to hydrodynamic models, Artificial Neural Networks applications for...journal article 2023
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