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Author : G. H. Hostetter,Mohammed S. Santina,Paul D'Carpio-Montalvo
Publisher : Unknown
Page : 520 pages
File Size : 52,7 Mb
Release : 1991
Category : Mathematics
ISBN : UOM:39015019397028
Author : Christian Constanda
Publisher : Springer Nature
Page : 261 pages
File Size : 44,8 Mb
Release : 2020-07-07
Category : Computers
ISBN : 9783030481865
This contributed volume collects papers presented at a special session of the conference Computational and Mathematical Methods in Science and Engineering (CMMSE) held in Cadiz, Spain from June 30 - July 6, 2019. Covering the applications of integral methods to scientific developments in a variety of fields, ranging from pure analysis to petroleum engineering, the chapters in this volume present new results in both pure and applied mathematics. Written by well-known researchers in their respective disciplines, each chapter shares a common methodology based on a combination of analytic and computational tools. This approach makes the collection a valuable, multidisciplinary reference on how mathematics can be applied to various real-world processes and phenomena. Computational and Analytic Methods in Science and Engineering will be ideal for applied mathematicians, physicists, and research engineers.
Author : Victor A. Bloomfield
Publisher : CRC Press
Page : 362 pages
File Size : 47,9 Mb
Release : 2018-09-03
Category : Mathematics
ISBN : 9781315360492
Instead of presenting the standard theoretical treatments that underlie the various numerical methods used by scientists and engineers, Using R for Numerical Analysis in Science and Engineering shows how to use R and its add-on packages to obtain numerical solutions to the complex mathematical problems commonly faced by scientists and engineers. This practical guide to the capabilities of R demonstrates Monte Carlo, stochastic, deterministic, and other numerical methods through an abundance of worked examples and code, covering the solution of systems of linear algebraic equations and nonlinear equations as well as ordinary differential equations and partial differential equations. It not only shows how to use R’s powerful graphic tools to construct the types of plots most useful in scientific and engineering work, but also: Explains how to statistically analyze and fit data to linear and nonlinear models Explores numerical differentiation, integration, and optimization Describes how to find eigenvalues and eigenfunctions Discusses interpolation and curve fitting Considers the analysis of time series Using R for Numerical Analysis in Science and Engineering provides a solid introduction to the most useful numerical methods for scientific and engineering data analysis using R.
Author : Said Gamil Ahmed,Hossein Jafari,Mukhtar Yagoub Youssif,Roberto Datja
Publisher : Bentham Science Publishers
Page : 280 pages
File Size : 54,5 Mb
Release : 2018-05-02
Category : Mathematics
ISBN : 9781681086514
This textbook is intended as a guide for undergraduate and graduate students in engineering, science and technology courses. Chapters of the book cover the numerical concepts of errors, approximations, differential equations and partial differential equations. The simple presentation of numerical concepts and illustrative examples helps students and general readers to understand the topics covered in the text.
Author : Siegmund Brandt
Publisher : Springer Science & Business Media
Page : 523 pages
File Size : 53,5 Mb
Release : 2014-02-14
Category : Science
ISBN : 9783319037622
The fourth edition of this successful textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Equal weight is given to statistical theory and practical problems. The concise mathematical treatment of the subject matter is illustrated by many examples and for the present edition a library of Java programs has been developed. It comprises methods of numerical data analysis and graphical representation as well as many example programs and solutions to programming problems. The book is conceived both as an introduction and as a work of reference. In particular it addresses itself to students, scientists and practitioners in science and engineering as a help in the analysis of their data in laboratory courses, in working for bachelor or master degrees, in thesis work, and in research and professional work.
Author : Johan Hoffman
Publisher : SIAM
Page : 425 pages
File Size : 49,5 Mb
Release : 2021-10-19
Category : Computers
ISBN : 9781611976724
Computational methods are an integral part of most scientific disciplines, and a rudimentary understanding of their potential and limitations is essential for any scientist or engineer. This textbook introduces computational science through a set of methods and algorithms, with the aim of familiarizing the reader with the field’s theoretical foundations and providing the practical skills to use and develop computational methods. Centered around a set of fundamental algorithms presented in the form of pseudocode, this self-contained textbook extends the classical syllabus with new material, including high performance computing, adjoint methods, machine learning, randomized algorithms, and quantum computing. It presents theoretical material alongside several examples and exercises and provides Python implementations of many key algorithms. Methods in Computational Science is for advanced undergraduate and graduate-level students studying computer science and data science. It can also be used to support continuous learning for practicing mathematicians, data scientists, computer scientists, and engineers in the field of computational science. It is appropriate for courses in advanced numerical analysis, data science, numerical optimization, and approximation theory.
Author : James P Howard, II
Publisher : CRC Press
Page : 257 pages
File Size : 51,6 Mb
Release : 2017-07-12
Category : Mathematics
ISBN : 9781498723640
Computational Methods for Numerical Analysis with R is an overview of traditional numerical analysis topics presented using R. This guide shows how common functions from linear algebra, interpolation, numerical integration, optimization, and differential equations can be implemented in pure R code. Every algorithm described is given with a complete function implementation in R, along with examples to demonstrate the function and its use. Computational Methods for Numerical Analysis with R is intended for those who already know R, but are interested in learning more about how the underlying algorithms work. As such, it is suitable for statisticians, economists, and engineers, and others with a computational and numerical background.
Author : Ralph E. White,Venkat R. Subramanian
Publisher : Springer Science & Business Media
Page : 871 pages
File Size : 41,7 Mb
Release : 2010-02-06
Category : Science
ISBN : 9783642043116
This book presents Maple solutions to a wide range of problems relevant to chemical engineers and others. Many of these solutions use Maple’s symbolic capability to help bridge the gap between analytical and numerical solutions. The readers are strongly encouraged to refer to the references included in the book for a better understanding of the physics involved, and for the mathematical analysis. This book was written for a senior undergraduate or a first year graduate student course in chemical engineering. Most of the examples in this book were done in Maple 10. However, the codes should run in the most recent version of Maple. We strongly encourage the readers to use the classic worksheet (*. mws) option in Maple as we believe it is more user-friendly and robust. In chapter one you will find an introduction to Maple which includes simple basics as a convenience for the reader such as plotting, solving linear and nonlinear equations, Laplace transformations, matrix operations, ‘do loop,’ and ‘while loop. ’ Chapter two presents linear ordinary differential equations in section 1 to include homogeneous and nonhomogeneous ODEs, solving systems of ODEs using the matrix exponential and Laplace transform method. In section two of chapter two, nonlinear ordinary differential equations are presented and include simultaneous series reactions, solving nonlinear ODEs with Maple’s ‘dsolve’ command, stop conditions, differential algebraic equations, and steady state solutions. Chapter three addresses boundary value problems.
Author : Christian Constanda,Paul Harris
Publisher : Springer
Page : 478 pages
File Size : 55,6 Mb
Release : 2019-07-18
Category : Mathematics
ISBN : 9783030160777
This contributed volume contains a collection of articles on state-of-the-art developments on the construction of theoretical integral techniques and their application to specific problems in science and engineering. The chapters in this book are based on talks given at the Fifteenth International Conference on Integral Methods in Science and Engineering, held July 16-20, 2018 at the University of Brighton, UK, and are written by internationally recognized researchers. The topics addressed are wide ranging, and include: Asymptotic analysis Boundary-domain integral equations Viscoplastic fluid flow Stationary waves Interior Neumann shape optimization Self-configuring neural networks This collection will be of interest to researchers in applied mathematics, physics, and mechanical and electrical engineering, as well as graduate students in these disciplines and other professionals for whom integration is an essential tool.
Author : Grant B. Gustafson,Calvin H. Wilcox
Publisher : Springer Science & Business Media
Page : 754 pages
File Size : 47,9 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781461206330
This book focuses on the topics which provide the foundation for practicing engineering mathematics: ordinary differential equations, vector calculus, linear algebra and partial differential equations. Destined to become the definitive work in the field, the book uses a practical engineering approach based upon solving equations and incorporates computational techniques throughout.
Author : T E Simos
Publisher : World Scientific
Page : 716 pages
File Size : 49,6 Mb
Release : 2003-08-26
Category : Mathematics
ISBN : 9789814485098
In the past few decades, many significant insights have been gained into several areas of computational methods in sciences and engineering. New problems and methodologies have appeared in some areas of sciences and engineering. There is always a need in these fields for the advancement of information exchange. The aim of this book is to facilitate the sharing of ideas, problems and methodologies between computational scientists and engineers in several disciplines. Extended abstracts of papers on the recent advances regarding computational methods in sciences and engineering are provided. The book briefly describes new methods in numerical analysis, computational mathematics, computational and theoretical physics, computational and theoretical chemistry, computational biology, computational mechanics, computational engineering, computational medicine, high performance computing, etc. Contents:Components for Time Series Receiver Clock Offset in GPS Solutions (P Abad)Some Numerical Methods for Stiff Problems (J C Butcher)Bifurcation Phenomena in Molecular Vibrational Spectroscopy (S C Farantos)Simulations of Spart in Random Fields (D T Hristopoulos)Electric Properties of Substituted Diacetylenes (P Karamanis & G Maroulis)Data Mining and Cryptology (E C Laskari et al.)A Finite Element Approach for the Dirac Radial Equation (L A A Nikolopoulos)Constraint Based Web Mining (I Petrounias et al.)Axisymmetric Rigid Bodies in Creeping Flow (J Roumeliotis)The Impact of Graphics Calculator on Mathematics Education in Asia (C-Y Suen)On the Systematic Construction of Molecular Basis Sets (S Wilson)and other papers Readership: Researchers and graduate students in any discipline involving scientific computation. Keywords:Numerical Analysis;Computational Mathematics;Computational and Theoretical Physics;Computational Chemistry;Computational Biology;Computational Mechanics;Computational Engineering, Computational Medicine;High Performance Computing
Author : Petre Teodorescu,Nicolae-Doru Stanescu,Nicolae Pandrea
Publisher : John Wiley & Sons
Page : 458 pages
File Size : 49,8 Mb
Release : 2013-05-07
Category : Computers
ISBN : 9781118614624
A much-needed guide on how to use numerical methods to solve practical engineering problems Bridging the gap between mathematics and engineering, Numerical Analysis with Applications in Mechanics and Engineering arms readers with powerful tools for solving real-world problems in mechanics, physics, and civil and mechanical engineering. Unlike most books on numerical analysis, this outstanding work links theory and application, explains the mathematics in simple engineering terms, and clearly demonstrates how to use numerical methods to obtain solutions and interpret results. Each chapter is devoted to a unique analytical methodology, including a detailed theoretical presentation and emphasis on practical computation. Ample numerical examples and applications round out the discussion, illustrating how to work out specific problems of mechanics, physics, or engineering. Readers will learn the core purpose of each technique, develop hands-on problem-solving skills, and get a complete picture of the studied phenomenon. Coverage includes: How to deal with errors in numerical analysis Approaches for solving problems in linear and nonlinear systems Methods of interpolation and approximation of functions Formulas and calculations for numerical differentiation and integration Integration of ordinary and partial differential equations Optimization methods and solutions for programming problems Numerical Analysis with Applications in Mechanics and Engineering is a one-of-a-kind guide for engineers using mathematical models and methods, as well as for physicists and mathematicians interested in engineering problems.
Author : Victor A. Bloomfield
Publisher : CRC Press
Page : 359 pages
File Size : 43,6 Mb
Release : 2018-09-03
Category : Mathematics
ISBN : 9781315362861
Instead of presenting the standard theoretical treatments that underlie the various numerical methods used by scientists and engineers, Using R for Numerical Analysis in Science and Engineering shows how to use R and its add-on packages to obtain numerical solutions to the complex mathematical problems commonly faced by scientists and engineers. This practical guide to the capabilities of R demonstrates Monte Carlo, stochastic, deterministic, and other numerical methods through an abundance of worked examples and code, covering the solution of systems of linear algebraic equations and nonlinear equations as well as ordinary differential equations and partial differential equations. It not only shows how to use R’s powerful graphic tools to construct the types of plots most useful in scientific and engineering work, but also: Explains how to statistically analyze and fit data to linear and nonlinear models Explores numerical differentiation, integration, and optimization Describes how to find eigenvalues and eigenfunctions Discusses interpolation and curve fitting Considers the analysis of time series Using R for Numerical Analysis in Science and Engineering provides a solid introduction to the most useful numerical methods for scientific and engineering data analysis using R.
Author : John H. Mathews
Publisher : Unknown
Page : 646 pages
File Size : 52,6 Mb
Release : 1992
Category : Numerical analysis
ISBN : 0136250475
A modern, computer-oriented approach to numerical analysis that shows how the mathematics of calculus and linear algebra are implemented in computer algorithms. Computer output is displayed in tables and used to develop topics of computer accuracy, pitfalls in computational methods and error estimation.
Author : Mark H. Holmes
Publisher : Springer Nature
Page : 563 pages
File Size : 42,9 Mb
Release : 2023-07-11
Category : Computers
ISBN : 9783031224300
This textbook provides an introduction to numerical computing and its applications in science and engineering. The topics covered include those usually found in an introductory course, as well as those that arise in data analysis. This includes optimization and regression-based methods using a singular value decomposition. The emphasis is on problem solving, and there are numerous exercises throughout the text concerning applications in engineering and science. The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used. The codes used for most of the computational examples in the text are available on GitHub. This new edition includes material necessary for an upper division course in computational linear algebra.