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Current Problems in Applied Mathematics and Computer Science and Systems [electronic resource] / edited by Anatoly Alikhanov, Pavel Lyakhov, Irina Samoylenko

Published
Cham : Springer Nature Switzerland : Imprint: Springer, 2023.
Edition
1st ed. 2023.
Physical Description
XIII, 522 p. 231 illus., 102 illus. in color. online resource
Additional Creators
Alikhanov, Anatoly, Lyakhov, Pavel, Samoylenko, Irina, and SpringerLink (Online service)
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Contents
Modeling of the potential dependence on the permittivity at the metal - dielectric medium interface -- Difference method for solving the Dirichlet problem for a multidimensional integro-differential equation of convection-diffusion -- The problem of restoring the unit of approximation in the model for studying functional dependence from approximate data -- RNS Reverse conversion algorithm and parity detection for the wide arbitrary moduli set -- Anomalous solute transport in an inhomogeneous porous medium taking into account mass transfer -- Determination of relaxation and flow coefficients during filtration of a homogeneous liquid in fractured-porous media -- Solution of the anomalous filtration problem in two-dimensional porous media -- On calculating the hyperbolic parameter of a two-dimensional lattice of linear comparison solutions -- Numerical solution of anomalous solute transport in a two-zone fractal porous medium -- Initial-boundary value problems for the loaded Hallaire equation with Gerasimov-Caputo fractional derivatives of different orders.
Summary
This book is based on the best papers accepted for presentation during the International Conference on Actual Problems of Applied Mathematics and Computer Systems (APAMCS-2022), Russia. The book includes research materials on modern mathematical problems, solutions in the field of scientific computing, data analysis and modular computing. The scope of numerical methods in scientific computing presents original research, including mathematical models and software implementations, related to the following topics: numerical methods in scientific computing; solving optimization problems; methods for approximating functions, etc. The studies in data analysis and modular computing include contributions in the field of deep learning, neural networks, mathematical statistics, machine learning methods, residue number system and artificial intelligence. Finally, the book gives insights into the fundamental problems in mathematics education. The book intends for readership specializing in the field of scientific computing, parallel computing, computer technology, machine learning, information security and mathematical education.
Subject(s)
ISBN
9783031341274
Digital File Characteristics
text file PDF
Part Of
Springer Nature eBook
View MARC record | catkey: 41083240