Sergiy Lyashko – författare

Mathematical methods in engineering are characterized by a wide range of techniques for approaching various problems. Moreover, completely different analysis techniques can be applied to the same problem, which is justified by the difference in specific applications. Therefore, the study of the analyses and solutions of specific problems leads the researcher to generate their own techniques for the analysis of similar problems continuously arising in the process of technical development.

Computational Methods and Mathematical Modeling in Cyberphysics and Engineering Applications contains solutions to specific problems in current areas of computational engineering and cyberphysics.

Mathematical methods in engineering are characterized by a wide range of techniques for approaching various problems. Moreover, completely different analysis techniques can be applied to the same problem, which is justified by the difference in specific applications. Therefore, the study of the analyses and solutions of specific problems leads the researcher to generate their own techniques for the analysis of similar problems continuously arising in the process of technical development.

Computational Methods and Mathematical Modeling in Cyberphysics and Engineering Applications contains solutions to specific problems in current areas of computational engineering and cyberphysics.

Situated at the intersection of advanced applied mathematics, computational science and engineering modeling, Computational Methods and Mathematical Modeling in Cyberphysics and Engineering Applications 2 presents contemporary analytical and numerical approaches to complex multiscale systems. This book develops a coherent framework for modeling coupled processes in porous media, heat and mass transfer, biodegradation-driven consolidation, and micro-irrigation networks, alongside modern operator-theoretic and variational methods in Banach spaces. It integrates finite element and finite difference techniques, quasiconformal mappings for electrical impedance tomography, fractional and biparabolic evolution equations, and homogenization in composite media. This book addresses high-performance and grid computing, geometric integration in Hamiltonian magnetic levitation systems, and hierarchical predictors for lossless image compression. It also explores AI-oriented transformer architectures for bioinformatics and optimization algorithms for variational inequalities. By combining rigorous mathematical foundations with scalable computational strategies, this book offers researchers and advanced practitioners a unified perspective on simulation, identification, and optimization in complex engineering and physical systems.

Responding to the growing demand for rigorous modeling frameworks capable of addressing complex technological challenges across disciplines, this book offers a coherent panorama of contemporary methodologies. These span lossless image compression algorithms, electrical impedance tomography and extragradient methods for variational inequalities in Banach spaces. It further examines multiphysics modeling in environmental engineering, grid-supported magnetic levitation systems and the optimization of water transport in porous media for sustainable irrigation. Foundational stochastic tools such as gamma processes and hidden Markov models for reliability and maintenance planning are integrated with theoretical advances, including matrix polynomials on noncommutative sets.

Responding to the growing demand for rigorous modeling frameworks capable of addressing complex technological challenges across disciplines, this book offers a coherent panorama of contemporary methodologies. These span lossless image compression algorithms, electrical impedance tomography and extragradient methods for variational inequalities in Banach spaces. It further examines multiphysics modeling in environmental engineering, grid-supported magnetic levitation systems and the optimization of water transport in porous media for sustainable irrigation. Foundational stochastic tools such as gamma processes and hidden Markov models for reliability and maintenance planning are integrated with theoretical advances, including matrix polynomials on noncommutative sets.

Mathematical methods in engineering are characterized by a wide range of techniques for approaching various problems. Moreover, completely different analysis techniques can be applied to the same problem, which is justified by the difference in specific applications. Therefore, the study of the analyses and solutions of specific problems leads the researcher to generate their own techniques for the analysis of similar problems continuously arising in the process of technical development.Computational Methods and Mathematical Modeling in Cyberphysics and Engineering Applications contains solutions to specific problems in current areas of computational engineering and cyberphysics.

Situated at the intersection of advanced applied mathematics, computational science and engineering modeling, Computational Methods and Mathematical Modeling in Cyberphysics and Engineering Applications 2 presents contemporary analytical and numerical approaches to complex multiscale systems. This book develops a coherent framework for modeling coupled processes in porous media, heat and mass transfer, biodegradation-driven consolidation, and micro-irrigation networks, alongside modern operator-theoretic and variational methods in Banach spaces. It integrates finite element and finite difference techniques, quasiconformal mappings for electrical impedance tomography, fractional and biparabolic evolution equations, and homogenization in composite media. This book addresses high-performance and grid computing, geometric integration in Hamiltonian magnetic levitation systems, and hierarchical predictors for lossless image compression. It also explores AI-oriented transformer architectures for bioinformatics and optimization algorithms for variational inequalities. By combining rigorous mathematical foundations with scalable computational strategies, this book offers researchers and advanced practitioners a unified perspective on simulation, identification, and optimization in complex engineering and physical systems.