Oscar Castillo Knihy

This book comprises a selection of papers from IFSA 2007 on theoretical advances and applications of fuzzy logic and soft computing. These papers were selected from over 400 submissions and constitute an important contribution to the theory and applications of fuzzy logic and soft computing methodologies. Soft Computing c- sists of several computing paradigms, including fuzzy logic, neural networks, genetic algorithms, and other techniques, which can be used to produce powerful intelligent systems for solving real-world problems. The papers of IFSA 2007 also make a c- tribution to this goal. This book is intended to be a major reference for scientists and engineers interested in applying new fuzzy logic and soft computing tools to achieve intelligent solution to complex problems. We consider that this book can also be used to get novel ideas for new lines of research, or to continue the lines of research proposed by the authors of the papers contained in the book. The book is divided in to sixteen main parts. Each part contains a set of papers on a common subject, so that the reader can find similar papers grouped together. Some of these parts are comprised from the papers of organized sessions of IFSA 2007 and we thank the session’s organizers for their incredible job on forming these sessions with invited and regular paper submissions.

The book explores innovative methods for developing intelligent systems through type-2 fuzzy logic and soft computing techniques. It emphasizes the integration of type-2 fuzzy logic with traditional approaches like neural networks and genetic algorithms to enhance hybrid systems. Key applications discussed include real-world pattern recognition challenges such as face, fingerprint, and voice recognition, as well as intelligent control and manufacturing. Aimed at scientists and engineers, it serves as a comprehensive reference for applying these advanced techniques in various fields.

Focusing on type-2 fuzzy controllers, the book explores their effectiveness in managing disturbances in mechanical systems, particularly hard or nonsmooth nonlinearities. It details the authors' research, showcasing models, simulations, and experiments involving servomotor control amidst dead-zone and Coulomb friction. Additionally, it addresses the control mechanisms for wheeled mobile robots and a biped robot, analyzing closed-loop systems through smooth and nonsmooth Lyapunov functions to enhance system stability and performance.

Focusing on type-3 fuzzy logic, this book explores its application in time series prediction, emphasizing its superiority in managing uncertainty for enhanced results. It integrates neural networks and fractal theory, presenting various hybrid intelligent methods tested on real-world prediction challenges such as COVID-19 and stock market trends. Aimed at scientists and engineers, it serves as a comprehensive reference for graduate courses in soft computing and related fields, while also inspiring new research avenues in intelligent prediction methodologies.

This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems.

This book reviews current state of the art methods for building intelligent systems using type-2 fuzzy logic and bio-inspired optimization techniques. Combining type-2 fuzzy logic with optimization algorithms, powerful hybrid intelligent systems have been built using the advantages that each technique offers. This book is intended to be a reference for scientists and engineers interested in applying type-2 fuzzy logic for solving problems in pattern recognition, intelligent control, intelligent manufacturing, robotics and automation. This book can also be used as a reference for graduate courses like the following: soft computing, intelligent pattern recognition, computer vision, applied artificial intelligence, and similar ones. We consider that this book can also be used to get novel ideas for new lines of re-search, or to continue the lines of research proposed by the authors.

This book describes in a detailed fashion the application of hybrid intelligent systems using soft computing techniques for intelligent control and mobile robotics. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The prudent combination of SC techniques can produce powerful hybrid intelligent systems that are capable of solving real-world problems. This is illustrated in this book with a wide range of applications, with particular emphasis in intelligent control and mobile robotics. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of theory and algorithms, which are basically papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of intelligent control, which are basically papers using bio-inspired techniques, like evolutionary algorithms and neural networks, for achieving intelligent control of non-linear plants. The third part contains papers with the theme of optimization of fuzzy controllers, which basically consider the application of bio-inspired optimization methods to automate the de-sign process of optimal type-1 and type-2 fuzzy controllers. The fourth part contains papers that deal with the application of SC techniques in times series prediction and intelligent agents. The fifth part contains papers with the theme of computer vision and robotics, which are papers considering soft computing methods for applications related to vision and robotics.

We describe in this book, new methods and applications of hybrid intelligent systems using soft computing techniques. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary al- rithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of intelligent control, which are basically papers that use hybrid systems to solve particular problems of control. The second part contains papers with the main theme of pattern recognition, which are basically papers using soft computing techniques for achieving pattern recognition in different applications. The third part contains papers with the themes of intelligent agents and social systems, which are papers that apply the ideas of agents and social behavior to solve real-world problems. The fourth part contains papers that deal with the hardware implementation of intelligent systems for solving particular problems. The fifth part contains papers that deal with modeling, simulation and optimization for real-world applications.

We describe in this book, new methods for building intelligent systems using type-2 fuzzy logic and soft computing techniques. Soft Computing (SC) consists of several computing paradigms, including type-1 fuzzy logic, neural networks, and genetic algorithms, which can be used to create powerful hybrid intelligent systems. In this book, we are extending the use of fuzzy logic to a higher order, which is called type-2 fuzzy logic. Combining type-2 fuzzy logic with traditional SC techniques, we can build powerful hybrid intelligent systems that can use the advantages that each te- nique offers. We consider in this book the use of type-2 fuzzy logic and traditional SC techniques to solve pattern recognition problems in real-world applications. We c- sider in particular the problems of face, fingerprint and voice recognition. We also consider the problem of recognizing a person by integrating the information given by the face, fingerprint and voice of the person. Other types of applications solved with type-2 fuzzy logic and SC techniques, include intelligent control, intelligent manuf- turing, and adaptive noise cancellation. This book is intended to be a major reference for scientists and engineers interested in applying type-2 fuzzy logic for solving problems in pattern recognition, intelligent control, intelligent manufacturing, robotics and automation.

This volume offers a general view of recent conceptual developments of Soft Computing (SC). It presents successful new applications of SC to real-world problems leading to better performance than "traditional" methods. The edited volume covers a wide spectrum of applications including areas such robotic dynamic systems, non-linear plants, manufacturing systems, and time series prediction.