Applied Mathematics and Computational Physics

As faster and more efficient numerical algorithms become available, the understanding of the physics and the mathematical foundation behind these new methods will play an increasingly important role. This Special Issue provides a platform for researchers from both academia and industry to present th...

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Бібліографічні деталі
Формат:	Online
Мова:	Англійська
Опубліковано:	MDPI - Multidisciplinary Digital Publishing Institute 2022
Предмети:	radial basis functions finite difference methods traveling waves non-uniform grids chaotic oscillator one-step method multi-step method computer arithmetic FPGA high strain rate impact modeling and simulation smoothed particle hydrodynamics finite element analysis hybrid nanofluid heat transfer non-isothermal shrinking surface MHD radiation multilayer perceptrons quaternion neural networks metaheuristic optimization genetic algorithms micropolar fluid constricted channel MHD pulsatile flow strouhal number flow pulsation parameter multiple integral finite volume method finite difference method Rosenau-KdV conservation solvability convergence transmission electron microscopy (TEM) convolutional neural networks (CNN) anomaly detection principal component analysis (PCA) machine learning deep learning neural networks Gallium-Arsenide (GaAs) radiation-based flowmeter two-phase flow feature extraction artificial intelligence time domain Boltzmann equation collision integral convolutional neural network annular regime scale layer-independent petroleum pipeline volume fraction dual energy technique prescribed heat flux similarity solutions dual solutions stability analysis RBF-FD node sampling lebesgue constant complex regions finite-difference methods data assimilation model order reduction finite elements analysis high dimensional data welding thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general thema EDItEUR::P Mathematics and Science
Онлайн доступ:	ONIX_20220111_9783036523057_775
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Applied Mathematics and Computational Physics

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