000 04122naaaa2201141uu 4500
001 https://directory.doabooks.org/handle/20.500.12854/76943
005 20220714184646.0
020 _abooks978-3-0365-2306-4
020 _a9783036523057
020 _a9783036523064
024 7 _a10.3390/books978-3-0365-2306-4
_cdoi
041 0 _aEnglish
042 _adc
072 7 _aGP
_2bicssc
072 7 _aP
_2bicssc
100 1 _aWood, Aihua
_4edt
_91606004
700 1 _aWood, Aihua
_4oth
_91606004
245 1 0 _aApplied Mathematics and Computational Physics
260 _aBasel, Switzerland
_bMDPI - Multidisciplinary Digital Publishing Institute
_c2021
300 _a1 electronic resource (273 p.)
506 0 _aOpen Access
_2star
_fUnrestricted online access
520 _aAs 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 their novel computational methods that have engineering and physics applications.
540 _aCreative Commons
_fhttps://creativecommons.org/licenses/by/4.0/
_2cc
_4https://creativecommons.org/licenses/by/4.0/
546 _aEnglish
650 7 _aResearch & information: general
_2bicssc
_9928234
650 7 _aMathematics & science
_2bicssc
_91014621
653 _aradial basis functions
653 _afinite difference methods
653 _atraveling waves
653 _anon-uniform grids
653 _achaotic oscillator
653 _aone-step method
653 _amulti-step method
653 _acomputer arithmetic
653 _aFPGA
653 _ahigh strain rate impact
653 _amodeling and simulation
653 _asmoothed particle hydrodynamics
653 _afinite element analysis
653 _ahybrid nanofluid
653 _aheat transfer
653 _anon-isothermal
653 _ashrinking surface
653 _aMHD
653 _aradiation
653 _amultilayer perceptrons
653 _aquaternion neural networks
653 _ametaheuristic optimization
653 _agenetic algorithms
653 _amicropolar fluid
653 _aconstricted channel
653 _aMHD pulsatile flow
653 _astrouhal number
653 _aflow pulsation parameter
653 _amultiple integral finite volume method
653 _afinite difference method
653 _aRosenau-KdV
653 _aconservation
653 _asolvability
653 _aconvergence
653 _atransmission electron microscopy (TEM)
653 _aconvolutional neural networks (CNN)
653 _aanomaly detection
653 _aprincipal component analysis (PCA)
653 _amachine learning
653 _adeep learning
653 _aneural networks
653 _aGallium-Arsenide (GaAs)
653 _aradiation-based flowmeter
653 _atwo-phase flow
653 _afeature extraction
653 _aartificial intelligence
653 _atime domain
653 _aBoltzmann equation
653 _acollision integral
653 _aconvolutional neural network
653 _aannular regime
653 _ascale layer-independent
653 _apetroleum pipeline
653 _avolume fraction
653 _adual energy technique
653 _aprescribed heat flux
653 _asimilarity solutions
653 _adual solutions
653 _astability analysis
653 _aRBF-FD
653 _anode sampling
653 _alebesgue constant
653 _acomplex regions
653 _afinite-difference methods
653 _adata assimilation
653 _amodel order reduction
653 _afinite elements analysis
653 _ahigh dimensional data
653 _awelding
856 4 0 _awww.oapen.org
_uhttps://mdpi.com/books/pdfview/book/4534
_70
_zDOAB: download the publication
856 4 0 _awww.oapen.org
_uhttps://directory.doabooks.org/handle/20.500.12854/76943
_70
_zDOAB: description of the publication
999 _c3006549
_d3006549