Suchergebnisse - Data-driven computational cost reduction
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Neural network design for data-driven prediction of target geometry for an aerodynamic inverse design algorithm
ISSN: 1738-494X, 1976-3824Veröffentlicht: Seoul Korean Society of Mechanical Engineers 01.08.2024Veröffentlicht in Journal of mechanical science and technology (01.08.2024)“… ) and long-short term memory (LSTM) network to predict the target geometry with early generated data of the design algorithm to reduce its computational cost …”
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Data-driven model reduction for the Bayesian solution of inverse problems
ISSN: 0029-5981, 1097-0207Veröffentlicht: Bognor Regis Blackwell Publishing Ltd 04.05.2015Veröffentlicht in International journal for numerical methods in engineering (04.05.2015)“… ) methods for posterior sampling. This paper proposes a data‐driven projection‐based model reduction technique to reduce this computational cost …”
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E-URES: Efficient User-Centric Residual-Echo Suppression Framework with a Data-Driven Approach to Reducing Computational Costs
ISSN: 2835-3439Veröffentlicht: IEEE 09.09.2024Veröffentlicht in International Workshop on Acoustic Signal Enhancement (09.09.2024)“… This paper introduces an efficient URES (E-URES) framework, which reduces computational costs in the final stage of the URES pipeline by minimizing the number of AECMOS computations …”
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Data driven surrogate modeling of horn antennas for optimal determination of radiation pattern and size using deep learning
ISSN: 0895-2477, 1098-2760Veröffentlicht: New York Wiley Subscription Services, Inc 01.01.2024Veröffentlicht in Microwave and optical technology letters (01.01.2024)“… Horn antenna designs are favored in many applications where ultra‐wide‐band operation range alongside of a high‐performance radiation pattern characteristics …”
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Data-driven model order reduction with proper symplectic decomposition for flexible multibody system
ISSN: 0924-090X, 1573-269XVeröffentlicht: Dordrecht Springer Netherlands 01.01.2022Veröffentlicht in Nonlinear dynamics (01.01.2022)“… In order to save the computational cost for simulating flexible multibody system, a novel model order reduction strategy based on the idea of data-driven model is proposed …”
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Surrogate Model Based on Data-Driven Model Reduction for Inelastic Behavior of Composite Microstructure
ISSN: 2093-274X, 2093-2480Veröffentlicht: Seoul The Korean Society for Aeronautical & Space Sciences (KSAS) 01.07.2023Veröffentlicht in International journal of aeronautical and space sciences (01.07.2023)“… However, a significant computational cost may be incurred owing to the iterative procedure when considering the inelastic behavior of composite materials …”
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Encoder–Decoder Convolutional Neural Networks for Flow Modeling in Unsaturated Porous Media: Forward and Inverse Approaches
ISSN: 2073-4441, 2073-4441Veröffentlicht: Basel MDPI AG 01.08.2023Veröffentlicht in Water (Basel) (01.08.2023)“… Data-driven modeling offers a faster and more efficient way to estimate soil moisture dynamics, significantly reducing computational costs …”
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A hybrid data-driven model order reduction strategy for flexible multibody systems considering impact and friction
ISSN: 0094-114XVeröffentlicht: Elsevier Ltd 01.03.2022Veröffentlicht in Mechanism and machine theory (01.03.2022)“… In this work, the nonsmooth contact method (NSCM) for FMBSs is briefly introduced. Moreover, in order to save the computational costs of a contact FMBS, a novel hybrid model order reduction (MOR …”
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Data-driven models for crashworthiness optimisation: intrusive and non-intrusive model order reduction techniques
ISSN: 1615-147X, 1615-1488Veröffentlicht: Berlin/Heidelberg Springer Berlin Heidelberg 01.07.2022Veröffentlicht in Structural and multidisciplinary optimization (01.07.2022)“… Therefore, data-driven Model Order Reduction (MOR) aims at generating low-fidelity models that approximate the solution while strongly reducing the computational cost …”
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Data-driven modelling of fully nonlinear wave loads on offshore wind-turbine monopiles at prototype scale
ISSN: 0951-8339Veröffentlicht: Elsevier Ltd 15.04.2025Veröffentlicht in Marine structures (15.04.2025)“… These approaches offer substantial reductions in computational cost while maintaining reasonable predictive accuracy for high-order wave loadings under a range …”
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Uncertain dynamics characteristic forecasting in composite plates with multi-defects of electric aircraft via physics-augmented meta-learning
ISSN: 1270-9638Veröffentlicht: Elsevier Masson SAS 01.09.2025Veröffentlicht in Aerospace science and technology (01.09.2025)“… •The effectiveness of the PMF has been verified through comparison with physics-data driven models …”
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A Hybrid Approach for Process Monitoring: Improving Data-Driven Methodologies With Dataset Size Reduction and Interval-Valued Representation
ISSN: 1530-437X, 1558-1748Veröffentlicht: New York IEEE 01.09.2020Veröffentlicht in IEEE sensors journal (01.09.2020)“… Kernel principal component analysis (KPCA) is a well-established data-driven process modeling and monitoring framework that has long been praised for its performances …”
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Data-driven prognostics based on time-frequency analysis and symbolic recurrent neural network for fuel cells under dynamic load
ISSN: 0951-8320, 1879-0836Veröffentlicht: Elsevier Ltd 01.05.2023Veröffentlicht in Reliability engineering & system safety (01.05.2023)“… ). For the prognostics of PEMFC operating under dynamic load, the challenges come from extracting degradation features, improving prediction accuracy, expanding the prognostics horizon, and reducing computational cost …”
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Data-driven reduced-order models via regularised Operator Inference for a single-injector combustion process
ISSN: 0303-6758, 1175-8899, 1175-8899Veröffentlicht: Wellington Taylor & Francis 01.06.2021Veröffentlicht in Journal of the Royal Society of New Zealand (01.06.2021)“… This paper derives predictive reduced-order models for rocket engine combustion dynamics via Operator Inference, a scientific machine learning approach that blends data-driven learning with physics-based modelling …”
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Using proper orthogonal decomposition for data-driven model error correction for heat conduction problems with uncertain boundary conditions
ISSN: 0307-904XVeröffentlicht: Elsevier Inc 01.10.2025Veröffentlicht in Applied mathematical modelling (01.10.2025)“… Reduced order modelling, often involving dimensionality reduction, together with data-driven model error correction, can make it possible to achieve both objectives …”
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Data-driven model reduction, Wiener projections, and the Koopman-Mori-Zwanzig formalism
ISSN: 0021-9991, 1090-2716Veröffentlicht: Cambridge Elsevier Inc 01.01.2021Veröffentlicht in Journal of computational physics (01.01.2021)“… •Data-driven model reduction for deterministic and random dynamical systems.•A precise formulation of data-driven modeling based on discrete-time Mori-Zwanzig formalism …”
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Data-driven uncertainty quantification in computational human head models
ISSN: 0045-7825, 1879-2138Veröffentlicht: Amsterdam Elsevier B.V 01.08.2022Veröffentlicht in Computer methods in applied mechanics and engineering (01.08.2022)“… Modern biofidelic head model simulations are associated with very high computational cost and high-dimensional inputs and outputs, which limits the applicability of traditional UQ methods …”
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Low-cost data-driven modelling of microwave components using domain confinement and PCA-based dimensionality reduction
ISSN: 1751-8725, 1751-8733Veröffentlicht: The Institution of Engineering and Technology 28.10.2020Veröffentlicht in IET microwaves, antennas & propagation (28.10.2020)“… Fast data-driven surrogate models can be employed as replacements of computationally demanding full-wave electromagnetic simulations to facilitate the microwave design procedures …”
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Data-driven molecular modeling with the generalized Langevin equation
ISSN: 0021-9991, 1090-2716Veröffentlicht: Cambridge Elsevier Inc 01.10.2020Veröffentlicht in Journal of computational physics (01.10.2020)“… •Data-driven GLE approximation balances computational cost and accuracy.•Accuracy tunable by adjusting order of memory kernel approximation …”
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Hybridization of data-driven threshold algorithm with fuzzy particle swarm optimization technique for gene selection in microarray data
ISSN: 2468-2276, 2468-2276Veröffentlicht: Elsevier B.V 01.03.2024Veröffentlicht in Scientific African (01.03.2024)“… ) optimisation capabilities. The proposed hybrid method serves multiple objectives, including minimizing the number of selected genes for model training, reducing computational costs, assessing each gene's contribution …”
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