The Improved Residual Power Series Method For Boundary Value Problems
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The Improved Residual Power Series Method for Boundary Value Problems
This book introduces a semi- analytical method, Improved Residual Power Series Method (IRPSM), for solving boundary value problems (BVPs). Unlike traditional numerical and analytical techniques, IRPSM offers quick convergence and minimal computational time, avoiding the pitfalls of round- off errors, linearization, perturbation, and discretization. This innovative approach has been rigorously compared with existing methods, demonstrating superior accuracy and efficiency. The book is meant for scholars, researchers, and students in mathematics, engineering, and physics. This book: Explores the application of IRPSM to a wide range of problems, including ordinary and partial differential equations, multi- point BVPs, and complex systems in physics and engineering Highlights IRPSM for its ability to efficiently handle highly nonlinear and complex boundary value problems, providing accurate solutions with reduced computational effort Demonstrates the method’s applicability across disciplines such as fluid dynamics and engineering Provides Mathematica codes for each solved problem, allowing readers to understand the solution procedure and implement IRPSM in their own research Offers a new and efficient method for solving BVPs and a practical reference for those seeking to minimize computational time and error in their work.
Fuzzy Differential Equations in Various Approaches
This book may be used as reference for graduate students interested in fuzzy differential equations and researchers working in fuzzy sets and systems, dynamical systems, uncertainty analysis, and applications of uncertain dynamical systems. Beginning with a historical overview and introduction to fundamental notions of fuzzy sets, including different possibilities of fuzzy differentiation and metric spaces, this book moves on to an overview of fuzzy calculus thorough exposition and comparison of different approaches. Innovative theories of fuzzy calculus and fuzzy differential equations using fuzzy bunches of functions are introduced and explored. Launching with a brief review of essential theories, this book investigates both well-known and novel approaches in this field; such as the Hukuhara differentiability and its generalizations as well as differential inclusions and Zadeh’s extension. Through a unique analysis, results of all these theories are examined and compared.
Approximation Methods and Analytical Modeling Using Partial Differential Equations
Author: Tamara Fastovska
language: en
Publisher: Frontiers Media SA
Release Date: 2025-03-28
Adequate mathematical modeling is the key to success for many real-world projects in engineering, medicine, and other applied areas. As soon as an appropriate mathematical model is developed, it can be comprehensively analyzed by a broad spectrum of available mathematical methods. For example, compartmental models are widely used in mathematical epidemiology to describe the dynamics of infectious diseases and in mathematical models of population genetics. While the existence of an optimal solution under certain condition can be often proved rigorously, this does not always mean that such a solution is easy to implement in practice. Finding a reasonable approximation can in itself be a challenging research problem. This Research Topic is devoted to modeling, analysis, and approximation problems whose solutions exploit and explore the theory of partial differential equations. It aims to highlight new analytical tools for use in the modeling of problems arising in applied sciences and practical areas. Researchers are invited to submit articles that investigate the qualitative behavior of weak solutions (removability conditions for singularities), the dependence of the local asymptotic property of these solutions on initial and boundary data, and also the existence of solutions. Contributors are particularly encouraged to focus on anisotropic models: analyzing the preconditions on the strength of the anisotropy, and comparing the analytical estimates for the growth behavior of the solutions near the singularities with the observed growth in numerical simulations. The qualitative analysis and analytical results should be confirmed by the numerically observed solution behavior.