Results 211 to 220 of about 395,716 (259)

Research on precision prediction of heavy-duty lathes based on hybrid PINNS neural network. [PDF]

Sci Rep
Wang R, Jing H, Yang M.
europepmc   +1 more source

Nonlinear Contributions of NO _<i>x</i> and Volatile Chemical Products to Air Pollution and the Associated Acute Premature Mortality. [PDF]

ACS EST Air
Liu J, Capps SL.
europepmc   +1 more source

A Physics-Informed Manifold Neural Operator Framework for Multi-Parameter Prediction of Polymer Aging in HTPB Solid Propellants. [PDF]

Polymers (Basel)
Liu S, Qiang H, Geng T, Wang X, Pei S, Ju X.   +5 more
europepmc   +1 more source

Scalable modeling of multi-spin ensembles in SABRE hyperpolarization: a symmetry-based framework for zero and ultralow fields. [PDF]

Magn Reson (Gott)
Markelov D, Snadin A, Kiryutin A, Barskiy D, Yurkovskaya A.   +4 more
europepmc   +1 more source

TF-DWGNet: a directed weighted graph neural network with tensor fusion for multi-omics cancer subtype classification. [PDF]

NAR Genom Bioinform
Yang T, Chen Z.
europepmc   +1 more source

Integrated Dynamic Modeling and Ground Test Validation for Spacecraft Micro-Vibration Suppression Considering Disturbance, Isolation, and Pointing Control. [PDF]

Sensors (Basel)
Wang H, Yan H, Tian L, Zang X, Zu Y.
europepmc   +1 more source

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Reduced order modeling in iTOUGH2

Computers & Geosciences, 2014
The inverse modeling and uncertainty quantification capabilities of iTOUGH2 are augmented with reduced order models (ROMs) that act as efficient surrogates for computationally expensive high fidelity models (HFMs). The implementation of the ROM capabilities involves integration of three main computational components.
George Shu Heng Pau, Yingqi Zhang, Stefan Finsterle, Haruko M. Wainwright, Jens T. Birkholzer   +4 more
openaire   +1 more source

On Synthesis of Reduced Order Models

2011
A framework for model reduction and synthesis is presented, which enables the re-use of reduced order models in circuit simulation. Two synthesis techniques are considered for obtaining the circuit representation (netlist) of the reduced model: (1) by means of realizing the reduced transfer function and (2) by unstamping the reduced system matrices ...
Ionutiu, R., Rommes, J.
openaire   +1 more source

Reduced-order modeling for hyperthermia control

IEEE Transactions on Biomedical Engineering, 1992
This paper analyzes the feasibility of using reduced-order modeling techniques in the design of multiple-input, multiple-output (MIMO) hyperthermia temperature controllers. State space thermal models are created based upon a finite difference expansion of the bioheat transfer equation model of a scanned focused ultrasound system (SFUS).
J. Kyle Potocki, Hal S. Tharp
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Reduced-Order Models for MEMS Applications

Nonlinear Dynamics, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Nayfeh, Ali H., Younis, Mohammad I., Abdel-Rahman, Eihab M.   +2 more
openaire   +2 more sources