Soft Numerical Computing In Uncertain Dynamic Systems
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| Author | : Tofigh Allahviranloo |
| Publisher | : Academic Press |
| Total Pages | : 390 |
| Release | : 2020-08-19 |
| Genre | : Computers |
| ISBN | : 0128229942 |
Soft Numerical Computing in Uncertain Dynamic Systems is intended for system specialists interested in dynamic systems that operate at different time scales. The book discusses several types of errors and their propagation, covering numerical methods—including convergence and consistence properties and characteristics—and proving of related theorems within the setting of soft computing. Several types of uncertainty representation like interval, fuzzy, type 2 fuzzy, granular, and combined uncertain sets are discussed in detail. The book can be used by engineering students in control and finite element fields, as well as all engineering, applied mathematics, economics, and computer science students. One of the important topics in applied science is dynamic systems and their applications. The authors develop these models and deliver solutions with the aid of numerical methods. Since they are inherently uncertain, soft computations are of high relevance here. This is the reason behind investigating soft numerical computing in dynamic systems. If these systems are involved with complex-uncertain data, they will be more practical and important. Real-life problems work with this type of data and most of them cannot be solved exactly and easily—sometimes they are impossible to solve. Clearly, all the numerical methods need to consider error of approximation. Other important applied topics involving uncertain dynamic systems include image processing and pattern recognition, which can benefit from uncertain dynamic systems as well. In fact, the main objective is to determine the coefficients of a matrix that acts as the frame in the image. One of the effective methods exhibiting high accuracy is to use finite differences to fill the cells of the matrix. - Explores dynamic models, how time is fundamental to the structure of the model and data, and how a process unfolds - Investigates the dynamic relationships between multiple components of a system in modeling using mathematical models and the concept of stability in uncertain environments - Exposes readers to many soft numerical methods to simulate the solution function's behavior
| Author | : Snehashish Chakraverty |
| Publisher | : John Wiley & Sons |
| Total Pages | : 464 |
| Release | : 2020-06-02 |
| Genre | : Mathematics |
| ISBN | : 1119585619 |
Brings mathematics to bear on your real-world, scientific problems Mathematical Methods in Interdisciplinary Sciences provides a practical and usable framework for bringing a mathematical approach to modelling real-life scientific and technological problems. The collection of chapters Dr. Snehashish Chakraverty has provided describe in detail how to bring mathematics, statistics, and computational methods to the fore to solve even the most stubborn problems involving the intersection of multiple fields of study. Graduate students, postgraduate students, researchers, and professors will all benefit significantly from the author's clear approach to applied mathematics. The book covers a wide range of interdisciplinary topics in which mathematics can be brought to bear on challenging problems requiring creative solutions. Subjects include: Structural static and vibration problems Heat conduction and diffusion problems Fluid dynamics problems The book also covers topics as diverse as soft computing and machine intelligence. It concludes with examinations of various fields of application, like infectious diseases, autonomous car and monotone inclusion problems.
| Author | : S. Chakraverty |
| Publisher | : Springer Nature |
| Total Pages | : 264 |
| Release | : 2021-11-01 |
| Genre | : Technology & Engineering |
| ISBN | : 9811647135 |
This book meets the present and future needs for the interaction between various science and technology/engineering areas on the one hand and different branches of soft computing on the other. Soft computing is the recent development about the computing methods which include fuzzy set theory/logic, evolutionary computation (EC), probabilistic reasoning, artificial neural networks, machine learning, expert systems, etc. Soft computing refers to a partnership of computational techniques in computer science, artificial intelligence, machine learning, and some other engineering disciplines, which attempt to study, model, and analyze complex problems from different interdisciplinary problems. This, as opposed to traditional computing, deals with approximate models and gives solutions to complex real-life problems. Unlike hard computing, soft computing is tolerant of imprecision, uncertainty, partial truth, and approximations. Interdisciplinary sciences include various challenging problems of science and engineering. Recent developments in soft computing are the bridge to handle different interdisciplinary science and engineering problems. In recent years, the correspondingly increased dialog between these disciplines has led to this new book. This is done, firstly, by encouraging the ways that soft computing may be applied in traditional areas, as well as point towards new and innovative areas of applications and secondly, by encouraging other scientific disciplines to engage in a dialog with the above computation algorithms outlining their problems to both access new methods as well as to suggest innovative developments within itself.
| Author | : Pandian Vasant |
| Publisher | : IGI Global |
| Total Pages | : 1173 |
| Release | : 2013-08-31 |
| Genre | : Technology & Engineering |
| ISBN | : 1466644516 |
"This book explores emerging technologies and best practices designed to effectively address concerns inherent in properly optimizing advanced systems, demonstrating applications in areas such as bio-engineering, space exploration, industrial informatics, information security, and nuclear and renewable energies"--Provided by publisher.
| Author | : Singh, Uday Pratap |
| Publisher | : IGI Global |
| Total Pages | : 409 |
| Release | : 2018-02-09 |
| Genre | : Computers |
| ISBN | : 1522535322 |
A critical part of ensuring that systems are advancing alongside technology without complications is problem solving. Practical applications of problem-solving theories can model conflict and cooperation and aid in creating solutions to real-world problems. Soft-Computing-Based Nonlinear Control Systems Design is a critical scholarly publication that examines the practical applications of control theory and its applications in problem solving to fields including economics, environmental management, and financial modelling. Featuring a wide range of topics, such as fuzzy logic, nature-inspired algorithms, and cloud computing, this book is geared toward academicians, researchers, and students seeking relevant research on control theory and its practical applications.
| Author | : Yury Tiumentsev |
| Publisher | : Academic Press |
| Total Pages | : 334 |
| Release | : 2019-05-17 |
| Genre | : Science |
| ISBN | : 0128154306 |
Neural Network Modeling and Identification of Dynamical Systems presents a new approach on how to obtain the adaptive neural network models for complex systems that are typically found in real-world applications. The book introduces the theoretical knowledge available for the modeled system into the purely empirical black box model, thereby converting the model to the gray box category. This approach significantly reduces the dimension of the resulting model and the required size of the training set. This book offers solutions for identifying controlled dynamical systems, as well as identifying characteristics of such systems, in particular, the aerodynamic characteristics of aircraft. - Covers both types of dynamic neural networks (black box and gray box) including their structure, synthesis and training - Offers application examples of dynamic neural network technologies, primarily related to aircraft - Provides an overview of recent achievements and future needs in this area
| Author | : Rafik Aziz Aliev |
| Publisher | : World Scientific |
| Total Pages | : 538 |
| Release | : 2017-12-06 |
| Genre | : Computers |
| ISBN | : 9813228954 |
Uncertain computation is a system of computation and reasoning in which the objects of computation are not values of variables but restrictions on values of variables.This compendium includes uncertain computation examples based on interval arithmetic, probabilistic arithmetic, fuzzy arithmetic, Z-number arithmetic, and arithmetic with geometric primitives.The principal problem with the existing decision theories is that they do not have capabilities to deal with such environment. Up to now, no books where decision theories based on all generalizations level of information are considered. Thus, this self-containing volume intends to overcome this gap between real-world settings' decisions and their formal analysis.
| Author | : Ivan Lirkov |
| Publisher | : Springer |
| Total Pages | : 607 |
| Release | : 2018-01-10 |
| Genre | : Computers |
| ISBN | : 3319734415 |
This book constitutes the thoroughly refereed post-conference proceedings of the 11th International Conference on Large-Scale Scientific Computations, LSSC 2017, held in Sozopol, Bulgaria, in June 2017. The 63 revised short papers together with 3 full papers presented were carefully reviewed and selected from 63 submissions. The conference presents results from the following topics: Hierarchical, adaptive, domain decomposition and local refinement methods; Robust preconditioning algorithms; Monte Carlo methods and algorithms; Numerical linear algebra; Control and optimization; Parallel algorithms and performance analysis; Large-scale computations of environmental, biomedical and engineering problems. The chapter 'Parallel Aggregation Based on Compatible Weighted Matching for AMG' is available open access under a CC BY 4.0 license.
| Author | : Chakraverty, S. |
| Publisher | : IGI Global |
| Total Pages | : 442 |
| Release | : 2014-01-31 |
| Genre | : Mathematics |
| ISBN | : 1466649925 |
"This book provides the reader with basic concepts for soft computing and other methods for various means of uncertainty in handling solutions, analysis, and applications"--Provided by publisher.
| Author | : Snehashish Chakraverty |
| Publisher | : Springer Nature |
| Total Pages | : 152 |
| Release | : 2022-05-31 |
| Genre | : Mathematics |
| ISBN | : 3031024249 |
Uncertainty is an inseparable component of almost every measurement and occurrence when dealing with real-world problems. Finding solutions to real-life problems in an uncertain environment is a difficult and challenging task. As such, this book addresses the solution of uncertain static and dynamic problems based on affine arithmetic approaches. Affine arithmetic is one of the recent developments designed to handle such uncertainties in a different manner which may be useful for overcoming the dependency problem and may compute better enclosures of the solutions. Further, uncertain static and dynamic problems turn into interval and/or fuzzy linear/nonlinear systems of equations and eigenvalue problems, respectively. Accordingly, this book includes newly developed efficient methods to handle the said problems based on the affine and interval/fuzzy approach. Various illustrative examples concerning static and dynamic problems of structures have been investigated in order to show the reliability and efficacy of the developed approaches.
