A First Course in Fuzzy Logic, Fuzzy Dynamical Systems, and Biomathematics PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download A First Course in Fuzzy Logic, Fuzzy Dynamical Systems, and Biomathematics PDF full book. Access full book title A First Course in Fuzzy Logic, Fuzzy Dynamical Systems, and Biomathematics by Laécio Carvalho de Barros. Download full books in PDF and EPUB format.
Author: Laécio Carvalho de Barros
Publisher: Springer Nature
ISBN: 3031504925
Category :
Languages : en
Pages : 324
Get Book Here
Book Description
Author: Laécio Carvalho de Barros
Publisher: Springer Nature
ISBN: 3031504925
Category :
Languages : en
Pages : 324
Get Book Here
Book Description
Author: Laécio Carvalho de Barros
Publisher: Springer
ISBN: 3662533243
Category : Technology & Engineering
Languages : en
Pages : 304
Get Book Here
Book Description
This book provides an essential introduction to the field of dynamical models. Starting from classical theories such as set theory and probability, it allows readers to draw near to the fuzzy case. On one hand, the book equips readers with a fundamental understanding of the theoretical underpinnings of fuzzy sets and fuzzy dynamical systems. On the other, it demonstrates how these theories are used to solve modeling problems in biomathematics, and presents existing derivatives and integrals applied to the context of fuzzy functions. Each of the major topics is accompanied by examples, worked-out exercises, and exercises to be completed. Moreover, many applications to real problems are presented. The book has been developed on the basis of the authors’ lectures to university students and is accordingly primarily intended as a textbook for both upper-level undergraduates and graduates in applied mathematics, statistics, and engineering. It also offers a valuable resource for practitioners such as mathematical consultants and modelers, and for researchers alike, as it may provide both groups with new ideas and inspirations for projects in the fields of fuzzy logic and biomathematics.
Author: Carlile Lavor
Publisher: Springer
ISBN: 3319940155
Category : Mathematics
Languages : en
Pages : 408
Get Book Here
Book Description
This book celebrates the 50th anniversary of the Institute of Mathematics, Statistics and Scientific Computing (IMECC) of the University of Campinas, Brazil, by offering reviews of selected research developed at one of the most prestigious mathematics institutes in Latin America. Written by senior professors at the IMECC, it covers topics in pure and applied mathematics and statistics ranging from differential geometry, dynamical systems, Lie groups, and partial differential equations to computational optimization, mathematical physics, stochastic process, time series, and more. A report on the challenges and opportunities of research in applied mathematics - a highly active field of research in the country - and highlights of the Institute since its foundation in 1968 completes this historical volume, which is unveiled in the same year that the International Mathematical Union (IMU) names Brazil as a member of the Group V of countries with the most relevant contributions in mathematics.
Author: Guilherme A. Barreto
Publisher: Springer
ISBN: 3319953125
Category : Computers
Languages : en
Pages : 616
Get Book Here
Book Description
This book constitutes the thoroughly refereed proceedings of the 37th IFSA Conference, NAFIPS 2018, held in Fortaleza, Brazil, in July 2018. The 55 full papers presented were carefully reviewed and selected from 73 submissions. The papers deal with a large spectrum of topics, including theory and applications of fuzzy numbers and sets, fuzzy logic, fuzzy inference systems, fuzzy clustering, fuzzy pattern classification, neuro-fuzzy systems, fuzzy control systems, fuzzy modeling, fuzzy mathematical morphology, fuzzy dynamical systems, time series forecasting, and making decision under uncertainty.
Author: Stephen Lynch
Publisher: Springer
ISBN: 3319781456
Category : Mathematics
Languages : en
Pages : 668
Get Book Here
Book Description
This textbook provides a broad introduction to continuous and discrete dynamical systems. With its hands-on approach, the text leads the reader from basic theory to recently published research material in nonlinear ordinary differential equations, nonlinear optics, multifractals, neural networks, and binary oscillator computing. Dynamical Systems with Applications Using Python takes advantage of Python’s extensive visualization, simulation, and algorithmic tools to study those topics in nonlinear dynamical systems through numerical algorithms and generated diagrams. After a tutorial introduction to Python, the first part of the book deals with continuous systems using differential equations, including both ordinary and delay differential equations. The second part of the book deals with discrete dynamical systems and progresses to the study of both continuous and discrete systems in contexts like chaos control and synchronization, neural networks, and binary oscillator computing. These later sections are useful reference material for undergraduate student projects. The book is rounded off with example coursework to challenge students’ programming abilities and Python-based exam questions. This book will appeal to advanced undergraduate and graduate students, applied mathematicians, engineers, and researchers in a range of disciplines, such as biology, chemistry, computing, economics, and physics. Since it provides a survey of dynamical systems, a familiarity with linear algebra, real and complex analysis, calculus, and ordinary differential equations is necessary, and knowledge of a programming language like C or Java is beneficial but not essential.
Author: Stephen Lynch
Publisher: Birkhäuser
ISBN: 3319614851
Category : Mathematics
Languages : en
Pages : 590
Get Book Here
Book Description
This book provides an introduction to the theory of dynamical systems with the aid of the Mathematica® computer algebra package. The book has a very hands-on approach and takes the reader from basic theory to recently published research material. Emphasized throughout are numerous applications to biology, chemical kinetics, economics, electronics, epidemiology, nonlinear optics, mechanics, population dynamics, and neural networks. Theorems and proofs are kept to a minimum. The first section deals with continuous systems using ordinary differential equations, while the second part is devoted to the study of discrete dynamical systems.
Author: Tofigh Allahviranloo
Publisher: Academic Press
ISBN: 0128229942
Category : Computers
Languages : en
Pages : 390
Get Book Here
Book Description
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: Cengiz Kahraman
Publisher: Springer Nature
ISBN: 303170018X
Category :
Languages : en
Pages : 788
Get Book Here
Book Description
Author: Stefania Tomasiello
Publisher: Springer Nature
ISBN: 3030989747
Category : Technology & Engineering
Languages : en
Pages : 141
Get Book Here
Book Description
This book offers an essential introduction to fuzzy logic, starting with the classical notions and going through more advanced notions from the current state-of-the-art research. Each of the major topics is accompanied by examples, problems and Scilab codes. As a free open source software, Scilab offers everyone the chance to practice the concepts learned through the book. The book represents a synthesis of authors’ research and experience through the lectures delivered to university students. It is primarily intended as a textbook for upper-level undergraduates and graduates in computer science, mathematics, physics and engineering. It also represents a valuable resource for practitioners and researchers alike, bringing ideas for projects in the broad field of fuzzy logic.
Author: Julia Rayz
Publisher: Springer Nature
ISBN: 3030820998
Category : Technology & Engineering
Languages : en
Pages : 506
Get Book Here
Book Description
This book focuses on an overview of the AI techniques, their foundations, their applications, and remaining challenges and open problems. Many artificial intelligence (AI) techniques do not explain their recommendations. Providing natural-language explanations for numerical AI recommendations is one of the main challenges of modern AI. To provide such explanations, a natural idea is to use techniques specifically designed to relate numerical recommendations and natural-language descriptions, namely fuzzy techniques. This book is of interest to practitioners who want to use fuzzy techniques to make AI applications explainable, to researchers who may want to extend the ideas from these papers to new application areas, and to graduate students who are interested in the state-of-the-art of fuzzy techniques and of explainable AI—in short, to anyone who is interested in problems involving fuzziness and AI in general.
