Mathematical modelling

This book studies the theoretical aspects for a variety of coupled fractional differential systems involving Riemann-Liouville, Caputo, ?

In an increasingly globally-connected world, the ability to predict, monitor, and contain pandemics is essential to ensure the health and well-being of all.

This monograph offers a novel structural perspective on the modelling of engineering problems, utilizing abstract mathematics in the form of category theory.

This monograph offers a novel structural perspective on the modelling of engineering problems, utilizing abstract mathematics in the form of category theory.

The content of the book collects some contributions related to the talks presented during the INdAM Workshop "e;Fractional Differential Equations: Modelling, Discretization, and Numerical Solvers"e;, held in Rome, Italy, on July 12-14, 2021.

This book collects selected, peer-reviewed research presented at the 8th International Conference on Mathematics: Pure, Applied, and Computation, held in Lombok, Indonesia, on 30 September 2023.

This book introduces readers to the financial markets, derivatives, structured products and how the products are modelled and implemented by practitioners.

After a brief introduction to the main law of physics and fundamental concepts inherent in electromechanical conversion, Vector Control of Induction Machines introduces the standard mathematical models for induction machines - whichever rotor technology is used - as well as several squirrel-cage induction machine vector-control strategies.

Dynamic management of systems development is a precondition for the realization of sustainable system development.

The financial results of any manufacturing company can be dramatically impacted by the repetitive decisions required to control a complex production network be it a network of machines in a factory; a network of factories in a company; or a network of companies in a supply chain.

The field of large-scale dimensional metrology (LSM) deals with objects that have linear dimensions ranging from tens to hundreds of meters.

Fuel cells are widely regarded as the future of the power and transportation industries.

Replacement Models with Minimal Repair is a collection of works by several well-known specialists on the subject of minimal repair in replacement policies.

Reliability and Safety of Complex Technical Systems and Processes offers a comprehensive approach to the analysis, identification, evaluation, prediction and optimization of complex technical systems operation, reliability and safety.

Advanced Modeling and Optimization of Manufacturing Processes presents a comprehensive review of the latest international research and development trends in the modeling and optimization of manufacturing processes, with a focus on machining.

This book introduces the mathematical foundations of distributionally robust optimization (DRO) for decision-making problems with ambiguous uncertainties and applies them to tackle the critical challenge of energy storage sizing in renewable-integrated power systems, providing readers with an efficient and reliable approach to analyze and design real-world energy systems with uncertainties.

This book sheds light on systems that learn extensively, with purpose and naturally interact with humans.

This volume gathers selected papers presented at the ICMSQUARE 2023 - 12th International Conference on Mathematical Modeling in Physical Sciences held in Belgrade, Serbia from August 28-31, 2023.

This book explores the stability analysis of neural networks and evolving intelligent systems, focusing on their ability to adapt to changing environments.

This book pushes the limits of conventional MRI visualization methods by completely changing the medical imaging landscape and leads to innovations that will help patients and healthcare providers alike.

This book explores the stability analysis of neural networks and evolving intelligent systems, focusing on their ability to adapt to changing environments.

The focus of this book is on providing students with insights into geometry that can help them understand deep learning from a unified perspective.

This book contains original research papers presented at the International Conference on Mathematical Modelling, Applied Analysis and Computation, held at JECRC University, Jaipur, India, on 6-8 July, 2018.

This book discusses the latest progresses and developments on complex systems research and intends to give an exposure to prospective readers about the theoretical and practical aspects of mathematical modelling, numerical simulation and agent-based modelling frameworks.

This book deals with network representation learning.

This book comprises select peer-reviewed articles submitted for the proceedings of the International Conference on Mathematics and Computing (ICMC 2022), held by the School of Advanced Sciences, Vellore Institute of Technology, Vellore, India, in association with Ramanujan Mathematical Society, India, Cryptology Research Society of India and Society for Electronic Transactions and Security, India, from 6-8 January 2022.

This volume convenes carefully selected, peer-reviewed papers presented at the BIOMAT 2023 International Symposium, which was virtually held on November 6-9, 2023, with an organization staff based in Rio de Janeiro, Brazil.

This volume convenes carefully selected, peer-reviewed papers presented at the BIOMAT 2023 International Symposium, which was virtually held on November 6-9, 2023, with an organization staff based in Rio de Janeiro, Brazil.

This edited book provides a comprehensive framework for the integration of mathematical methodologies into biological research, emphasizing applications that directly address topics related to SDG 3 (Good Health and Well Being) and SDG 6 (Clean Water and Sanitation).

This volume gathers selected, peer-reviewed contributions presented at the 5th International Seminar on Mathematics in Industry – ISMI2024, held on September 9-11, 2024 in Kuala Lumpur, Malaysia.

This book is a comprehensive and time-tested guide to the mathematical theory of Fourier series and boundary value problems, with a strong emphasis on engineering applications.

The introduction of cross diffusivity opens many questions in the theory of reactiondiffusion systems.

Dynamics of Democratic Elections explores modeling approaches to democratic elections and opinion dynamics at the intersection of mathematics, political science, and computational modeling.

Dynamics of Democratic Elections explores modeling approaches to democratic elections and opinion dynamics at the intersection of mathematics, political science, and computational modeling.

Modelling Order and Disorder: Integro-Differential Nonlinear Equations provides an overview of a general mathematical structure: integro-differential nonlinear equations.

Modelling Order and Disorder: Integro-Differential Nonlinear Equations provides an overview of a general mathematical structure: integro-differential nonlinear equations.

Exact Methods for Nonlinear PDEs describes effective analytical methods for finding exact solutions to nonlinear differential equations of mathematical physics and other partial differential equations and also demonstrates the practical applications of these methods.

This book describes novel ways of using deep learning to solve real-world problems.

This book mainly provides recent advances in finite-time and fixed-time control issues for complex networks and neural networks.

This book mainly provides recent advances in finite-time and fixed-time control issues for complex networks and neural networks.

This book describes novel ways of using deep learning to solve real-world problems.

Welcome to the fascinating intersection of mathematics, biology, and ecology!

This book provides a direct method based on system solutions to address the problems related to the analysis and control of delayed neural networks.

This book provides a direct method based on system solutions to address the problems related to the analysis and control of delayed neural networks.

This book introduces approaches to generalize the benefits of equivariant deep learning to a broader set of learned structures through learned homomorphisms.