Scientific Computing Validated Numerics Interval Methods

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  • Author : Walter Krämer
  • Publisher : Springer Science & Business Media
  • Pages : 398 pages
  • ISBN : 1475764847
  • Rating : /5 from reviews
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Download or Read online Scientific Computing Validated Numerics Interval Methods full in PDF, ePub and kindle. this book written by Walter Krämer and published by Springer Science & Business Media which was released on 17 April 2013 with total page 398 pages. We cannot guarantee that Scientific Computing Validated Numerics Interval Methods book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. Scan 2000, the GAMM - IMACS International Symposium on Scientific Computing, Computer Arithmetic, and Validated Numerics and Interval 2000, the International Conference on Interval Methods in Science and Engineering were jointly held in Karlsruhe, September 19-22, 2000. The joint conference continued the series of 7 previous Scan-symposia under the joint sponsorship of GAMM and IMACS. These conferences have traditionally covered the numerical and algorithmic aspects of scientific computing, with a strong emphasis on validation and verification of computed results as well as on arithmetic, programming, and algorithmic tools for this purpose. The conference further continued the series of 4 former Interval conferences focusing on interval methods and their application in science and engineering. The objectives are to propagate current applications and research as well as to promote a greater understanding and increased awareness of the subject matters. The symposium was held in Karlsruhe the European cradle of interval arithmetic and self-validating numerics and attracted 193 researchers from 33 countries. 12 invited and 153 contributed talks were given. But not only the quantity was overwhelming we were deeply impressed by the emerging maturity of our discipline. There were many talks discussing a wide variety of serious applications stretching all parts of mathematical modelling. New efficient, publicly available or even commercial tools were proposed or presented, and also foundations of the theory of intervals and reliable computations were considerably strengthened.

Scientific Computing Validated Numerics Interval Methods

Scientific Computing  Validated Numerics  Interval Methods
  • Author : Walter Krämer,Jürgen Wolff von Gudenberg
  • Publisher : Springer Science & Business Media
  • Release : 17 April 2013
GET THIS BOOK Scientific Computing Validated Numerics Interval Methods

Scan 2000, the GAMM - IMACS International Symposium on Scientific Computing, Computer Arithmetic, and Validated Numerics and Interval 2000, the International Conference on Interval Methods in Science and Engineering were jointly held in Karlsruhe, September 19-22, 2000. The joint conference continued the series of 7 previous Scan-symposia under the joint sponsorship of GAMM and IMACS. These conferences have traditionally covered the numerical and algorithmic aspects of scientific computing, with a strong emphasis on validation and verification of computed results as well as on arithmetic,

Computational Interval Methods for Engineering Applications

Computational Interval Methods for Engineering Applications
  • Author : Snehashish Chakraverty,Nisha Rani Mahato
  • Publisher : Academic Press
  • Release : 01 November 2020
GET THIS BOOK Computational Interval Methods for Engineering Applications

Computational Interval Methods for Engineering Applications explains how to use classical and advanced interval arithmetic to solve differential equations for a wide range of scientific and engineering problems. In mathematical models where there are variables and parameters of uncertain value, interval methods can be used as an efficient tool for handling this uncertainty. In addition, it can produce rigorous enclosures of solutions of practical problems governed by mathematical equations. Other topics discussed in the book include linear differential equations in

Computational Complexity and Feasibility of Data Processing and Interval Computations

Computational Complexity and Feasibility of Data Processing and Interval Computations
  • Author : V. Kreinovich,A.V. Lakeyev,J. Rohn,P.T. Kahl
  • Publisher : Springer Science & Business Media
  • Release : 29 June 2013
GET THIS BOOK Computational Complexity and Feasibility of Data Processing and Interval Computations

Targeted audience • Specialists in numerical computations, especially in numerical optimiza tion, who are interested in designing algorithms with automatie result ver ification, and who would therefore be interested in knowing how general their algorithms caIi in principle be. • Mathematicians and computer scientists who are interested in the theory 0/ computing and computational complexity, especially computational com plexity of numerical computations. • Students in applied mathematics and computer science who are interested in computational complexity of different numerical methods and in learning general

Handbook of Granular Computing

Handbook of Granular Computing
  • Author : Witold Pedrycz,Andrzej Skowron,Vladik Kreinovich
  • Publisher : John Wiley & Sons
  • Release : 31 July 2008
GET THIS BOOK Handbook of Granular Computing

Although the notion is a relatively recent one, the notions and principles of Granular Computing (GrC) have appeared in a different guise in many related fields including granularity in Artificial Intelligence, interval computing, cluster analysis, quotient space theory and many others. Recent years have witnessed a renewed and expanding interest in the topic as it begins to play a key role in bioinformatics, e-commerce, machine learning, security, data mining and wireless mobile computing when it comes to the issues of

Computational Intelligence in Information Assurance and Security

Computational Intelligence in Information Assurance and Security
  • Author : Ajith Abraham
  • Publisher : Springer Science & Business Media
  • Release : 02 May 2007
GET THIS BOOK Computational Intelligence in Information Assurance and Security

This volume provides the academic and industrial community with a medium for presenting original research and applications related to information assurance and security using computational intelligence techniques. It details current research on information assurance and security regarding both the theoretical and methodological aspects, as well as various applications in solving real world problems using computational intelligence.

Engineering Applications of Neural Networks

Engineering Applications of Neural Networks
  • Author : Giacomo Boracchi,Lazaros Iliadis,Chrisina Jayne,Aristidis Likas
  • Publisher : Springer
  • Release : 30 July 2017
GET THIS BOOK Engineering Applications of Neural Networks

This book constitutes the refereed proceedings of the 18th International Conference on Engineering Applications of Neural Networks, EANN 2017, held in Athens, Greece, in August 2017. The 40 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 83 submissions. The papers cover the topics of deep learning, convolutional neural networks, image processing, pattern recognition, recommendation systems, machine learning, and applications of Artificial Neural Networks (ANN) applications in engineering, 5G telecommunication networks, and audio signal processing. The volume also includes

Computer Methods for Engineering with MATLAB Applications Second Edition

Computer Methods for Engineering with MATLAB   Applications  Second Edition
  • Author : Yogesh Jaluria
  • Publisher : CRC Press
  • Release : 08 September 2011
GET THIS BOOK Computer Methods for Engineering with MATLAB Applications Second Edition

Substantially revised and updated, Computer Methods for Engineering with MATLAB® Applications, Second Edition presents equations to describe engineering processes and systems. It includes computer methods for solving these equations and discusses the nature and validity of the numerical results for a variety of engineering problems. This edition now uses MATLAB in its discussions of computer solution. New to the Second Edition Recent advances in computational software and hardware A large number of MATLAB commands and programs for solving exercises and

Combining Interval Probabilistic and Other Types of Uncertainty in Engineering Applications

Combining Interval  Probabilistic  and Other Types of Uncertainty in Engineering Applications
  • Author : Andrew Pownuk,Vladik Kreinovich
  • Publisher : Springer
  • Release : 03 May 2018
GET THIS BOOK Combining Interval Probabilistic and Other Types of Uncertainty in Engineering Applications

How can we solve engineering problems while taking into account data characterized by different types of measurement and estimation uncertainty: interval, probabilistic, fuzzy, etc.? This book provides a theoretical basis for arriving at such solutions, as well as case studies demonstrating how these theoretical ideas can be translated into practical applications in the geosciences, pavement engineering, etc. In all these developments, the authors’ objectives were to provide accurate estimates of the resulting uncertainty; to offer solutions that require reasonably short

Soft Computing Approach for Mathematical Modeling of Engineering Problems

Soft Computing Approach for Mathematical Modeling of Engineering Problems
  • Author : Ali Ahmadian,Soheil Salahshour
  • Publisher : CRC Press
  • Release : 03 September 2021
GET THIS BOOK Soft Computing Approach for Mathematical Modeling of Engineering Problems

This book describes different mathematical modeling and soft computing techniques used to solve practical engineering problems. It gives an overview of the current state of soft computing techniques and describes the advantages and disadvantages of soft computing compared to traditional hard computing techniques. Through examples and case studies the editors demonstrate and describe how problems with inherent uncertainty can be addressed and eventually solved through the aid of numerical models and methods. The chapters address several applications and examples in

Scientific Computing Computer Arithmetic and Validated Numerics

Scientific Computing  Computer Arithmetic  and Validated Numerics
  • Author : Marco Nehmeier,Jürgen Wolff von Gudenberg,Warwick Tucker
  • Publisher : Springer
  • Release : 08 April 2016
GET THIS BOOK Scientific Computing Computer Arithmetic and Validated Numerics

This book constitutes the refereed post proceedings of the 16th International Symposium, SCAN 2014, held in Würzburg, Germany, in September 2014. The 22 full papers presented were carefully reviewed and selected from 60 submissions. The main concerns of research addressed by SCAN conferences are validation, verification or reliable assertions of numerical computations. Interval arithmetic and other treatments of uncertainty are developed as appropriate tools.

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications
  • Author : Arun Kumar Sangaiah,Zhiyong Zhang,Michael Sheng
  • Publisher : Academic Press
  • Release : 21 August 2018
GET THIS BOOK Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications

Computational Intelligence for Multimedia Big Data on the Cloud with Engineering Applications covers timely topics, including the neural network (NN), particle swarm optimization (PSO), evolutionary algorithm (GA), fuzzy sets (FS) and rough sets (RS), etc. Furthermore, the book highlights recent research on representative techniques to elaborate how a data-centric system formed a powerful platform for the processing of cloud hosted multimedia big data and how it could be analyzed, processed and characterized by CI. The book also provides a view

Uncertainty Quantification and Predictive Computational Science

Uncertainty Quantification and Predictive Computational Science
  • Author : Ryan G. McClarren
  • Publisher : Springer
  • Release : 23 November 2018
GET THIS BOOK Uncertainty Quantification and Predictive Computational Science

This textbook teaches the essential background and skills for understanding and quantifying uncertainties in a computational simulation, and for predicting the behavior of a system under those uncertainties. It addresses a critical knowledge gap in the widespread adoption of simulation in high-consequence decision-making throughout the engineering and physical sciences. Constructing sophisticated techniques for prediction from basic building blocks, the book first reviews the fundamentals that underpin later topics of the book including probability, sampling, and Bayesian statistics. Part II focuses

Numerical Validation in Current Hardware Architectures

Numerical Validation in Current Hardware Architectures
  • Author : Annie A.M. Cuyt,Walter Krämer,Wolfram Luther,Peter Markstein
  • Publisher : Springer
  • Release : 28 April 2009
GET THIS BOOK Numerical Validation in Current Hardware Architectures

This book constitutes the thoroughly refereed post-proceedings of the Dagstuhl Seminar 08021 on Numerical Validation in Current Hardware Architectures held at Dagstuhl Castle, Germany, in January 2008. The 16 revised full papers presented were selected during two rounds of reviewing and improvements. The papers are organized in topical sections on languages, software systems and tools, new verification techniques based on interval arithmetic, applications in science and engineering, and novel approaches to verification.

Advances in Computation and Intelligence

Advances in Computation and Intelligence
  • Author : Sanyou Zeng
  • Publisher : Springer
  • Release : 26 August 2007
GET THIS BOOK Advances in Computation and Intelligence

This book constitutes the refereed proceedings of the Second International Symposium on Intelligence Computation and Applications, ISICA 2007, held in Wuhan, China, in September 2007. The 71 revised full papers cover such topics as evolutionary computation, evolutionary learning, neural networks, swarms, pattern recognition, and data mining.