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Futuristic Trends in Numerical Relaying for Transmission Line Protections (Energy Systems in Electrical Engineering)
by Ujjaval Patel Praghnesh Bhatt Nilesh ChothaniThis book presents the state-of-the-art approach for transmission line protection schemes for smart power grid. It provides a comprehensive solution for real-time development of numerical relaying schemes for future power grids which can minimize cascade tripping and widespread blackout problems prevailing all around the world. The book also includes the traditional approach for transmission line protection along with issues and challenges in protection philosophy. It highlights the issues for sheltering power grid from unwanted hazards with very fundamental approach. The book follows a step-by-step approach for resolving critical issues like high impedance faults, power swing detection and auto-reclosing schemes with adaptive protection process. The book also covers the topic of hardware solution for real-time implementation of auto-reclosing scheme for transmission line protection schemes along with comparative analysis with the recently developed analytical approach such as Artificial Neural Network (ANN), Support Vector Machine (SVM) and other machine learning algorithms. It will be useful to researchers and industry professionals and students in the fields of power system protection.
El futuro es ahora: Un viaje a través de la realidad virtual
by Jaron LanierEl padre de la realidad virtual nos explica sus infinitas posibilidades a través de su experiencia con la tecnología. A través del fascinante recorrido de una vida dedicada a la tecnología, Jaron Lanier expone la capacidad de la realidad virtual para iluminar y amplificar la comprensión que tenemos de nuestra especie y ofrece a los lectores una nueva perspectiva sobre cómo el cerebro y el cuerpo humano se conectan al mundo. Al entender la realidad virtual como una aventura tanto científica como cultural, Lanier demuestra el componente humanístico que esta aporta a la tecnología. Si bien sus libros anteriores ofrecían una visión más crítica de las redes sociales y de otras manifestaciones de la tecnología, en El futuro es ahora el autor argumenta que la realidad virtual puede hacer que nuestra vida sea más rica y más completa. Una obra que no solo nos muestra qué significa ser humano en esta era de posibilidades tecnológicas sin precedentes, sino que también une la dimensión tecnológica con nuestra experiencia corporal. Reseñas:«Una historia maravillosa, profundamente humana y sumamente personal.»Dave Eggers «Es el padre de la realidad virtual y un genio de la tecnología punta.»Sunday Times «Una mente tan ilimitada como internet.»Evening Standard «Íntimo e idiosincrásico [...] peculiar y fascinante [...] La vívida imaginación de Lanier se convierte en un personaje más. Su visión es humanista e insiste en que el objetivo más importante del desarrollo de la realidad virtual debe ser la conexión humana.»The New York Times Book Review «Una lectura esencial, no solo para los conocedores de la realidad virtual, sino para cualquiera interesado en comprender cómo la sociedad ha llegado a convertirse en lo que es hoy en día y en qué podría convertirse en un futuro no tan lejano.»The Economist «Brillante e inspirador.»Publishers Weekly
Fuzzy-AI Model and Big Data Exploration: A Methodological Philosophy in Solving Problems in Digital Era
by Shaopei LinBased on the idea of a universal rule for problem solving, the book suggests that the “System-Fuzzy Approach (SFA)” Model can be applied to various complex real-world problems. It is the first book for problem solving in complicated problems with a universal project management tool. Systematic searching is an essential step in identifying the right direction in problem solving; and the fuzzy steps in concrete problem solving reflect the flexibility and compromises involved in the process. Nevertheless, the fuzzy steps also demonstrate human beings’ impressively flexible problem-solving skills. Simulating human decision-making processes based on fuzzy information processing is essential in our digital era, in which many problems need to be solved by means of artificial intelligence; hence the Fuzzy-AI Model emerged. As a universal rule and tool, it can be applied to a broad range of real-world problems. Offering a valuable guide to fuzzy decision-making, this book is intended for researchers, scientists and graduate students in the fields of Engineering, Economics, Sociology, Managerial Science, Project Management etc.
Fuzzy Analytic Hierarchy Process
by Ali Emrouznejad William HoThis book is the first in the literature to present the state of the art and some interesting and relevant applications of the Fuzzy Analytic Hierarchy Process (FAHP). The AHP is a conceptually and mathematically simple, easily implementable, yet extremely powerful tool for group decision making and is used around the world in a wide variety of decision situations, in fields such as government, business, industry, healthcare, and education. The aim of this book is to study various fuzzy methods for dealing with the imprecise and ambiguous data in AHP. Features: First book available on FAHP. Showcases state-of-the-art developments. Contains several novel real-life applications. Provides useful insights to both academics and practitioners in making group decisions under uncertainty This book provides the necessary background to work with existing fuzzy AHP models. Once the material in this book has been mastered, the reader will be able to apply fuzzy AHP models to his or her problems for making decisions with imprecise data.
Fuzzy and Multi-Level Decision Making: Soft Computing Approaches (Studies in Fuzziness and Soft Computing #368)
by Chi-Bin Cheng Hsu-Shih Shih E. Stanley LeeThis book offers a comprehensive overview of cutting-edge approaches for decision-making in hierarchical organizations. It presents soft-computing-based techniques, including fuzzy sets, neural networks, genetic algorithms and particle swarm optimization, and shows how these approaches can be effectively used to deal with problems typical of this kind of organization. After introducing the main classical approaches applied to multiple-level programming, the book describes a set of soft-computing techniques, demonstrating their advantages in providing more efficient solutions to hierarchical decision-making problems compared to the classical methods. Based on the book Fuzzy and Multi-Level Decision Making (Springer, 2001) by Lee E.S and Shih, H., this second edition has been expanded to include the most recent findings and methods and a broader spectrum of soft computing approaches. All the algorithms are presented in detail, together with a wealth of practical examples and solutions to real-world problems, providing students, researchers and professionals with a timely, practice-oriented reference guide to the area of interactive fuzzy decision making, multi-level programming and hierarchical optimization.
The Fuzzy and the Techie: Why the Liberal Arts Will Rule the Digital World
by Scott Hartley&“Artfully explains why it is time for us to get over the false division between the human and the technical.&”—Tim Brown, CEO of IDEO and author of Change by Design Scott Hartley first heard the terms fuzzy and techie while studying political science at Stanford University. If you majored in humanities or social sciences, you were a fuzzy. If you majored in computer or hard sciences, you were a techie. While Silicon Valley is generally considered a techie stronghold, the founders of companies like Airbnb, Pinterest, Slack, LinkedIn, PayPal, Stitch Fix, Reddit, and others are all fuzzies—in other words, people with backgrounds in the liberal arts. In this brilliantly counterintuitive book, Hartley shatters assumptions about business and education today: learning to code is not enough. The soft skills—curiosity, communication, and collaboration, along with an understanding of psychology and society&’s gravest problems—are central to why technology has value. Fuzzies are the instrumental stewards of robots, artificial intelligence, and machine learning. They offer a human touch that is of equal—if not greater—importance in our technology-led world than what most techies can provide. For anyone doubting whether a well-rounded liberal arts education is practical in today&’s world, Hartley&’s work will come as an inspiring revelation. Finalist for the 2016 Financial Times/McKinsey Bracken Bower Prize and A Financial Times Business Book of the Month
Fuzzy Approaches for Soft Computing and Approximate Reasoning: Dedicated to Bernadette Bouchon-Meunier (Studies in Fuzziness and Soft Computing #394)
by Marie-Jeanne Lesot Christophe MarsalaThis book gathers cutting-edge papers in the area of Computational Intelligence, presented by specialists, and covering all major trends in the research community in order to provide readers with a rich primer. It presents an overview of various soft computing topics and approximate reasoning-based approaches, both from theoretical and applied perspectives. Numerous topics are covered: fundamentals aspects of fuzzy sets theory, reasoning approaches (interpolative, analogical, similarity-based), decision and optimization theory, fuzzy databases, soft machine learning, summarization, interpretability and XAI. Moreover, several application-based papers are included, e.g. on image processing, semantic web and intelligent tutoring systems. This book is dedicated to Bernadette Bouchon-Meunier in honor of her achievements in Computational Intelligence, which, throughout her career, have included profuse and diverse collaborations, both thematically and geographically.
Fuzzy Cognitive Maps: Best Practices and Modern Methods
by Philippe J. Giabbanelli Gonzalo NápolesThis book starts with the rationale for creating an FCM by contrast to other techniques for participatory modeling, as this rationale is a key element to justify the adoption of techniques in a research paper. Fuzzy cognitive mapping is an active research field with over 20,000 publications devoted to externalizing the qualitative perspectives or “mental models” of individuals and groups. Since the emergence of fuzzy cognitive maps (FCMs) back in the 80s, new algorithms have been developed to reduce bias, facilitate the externalization process, or efficiently utilize quantitative data via machine learning. It covers the development of an FCM with participants through a traditional in-person setting, drawing from the experience of practitioners and highlighting solutions to commonly encountered challenges. The book continues with introducing principles of simulations with FCMs as a tool to perform what-if scenario analysis, while extending those principles to more elaborated simulation scenarios where FCMs and agent-based modeling are combined. Once an FCM model is obtained, the book then details the analytical tools available for practitioners (e.g., to identify the most important factors) and provides examples to aid in the interpretation of results. The discussion concerning relevant extensions is equally pertinent, which are devoted to increasing the expressiveness of the FCM formalism in problems involving uncertainty. The last four chapters focus on building FCM models from historical data. These models are typically needed when facing multi-output prediction or pattern classification problems. In that regard, the book smoothly guides the reader from simple approaches to more elaborated algorithms, symbolizing the noticeable progress of this field in the last 35 years. Problems, recent references, and functional codes are included in each chapter to provide practice and support further learning from practitioners and researchers.
Fuzzy Cognitive Maps: A Tool for the Modeling and Simulation of Processes and Systems (Studies in Fuzziness and Soft Computing #427)
by László T. KóczyThis book is considered as a monograph but also as a potential textbook for graduate students, focusing on the application of FCMs for modelling and analysing the behaviour of multicomponent systems. In the last two decades, no monograph or textbook has been published on the topic Fuzzy Cognitive Maps (FCM), so this new book is definitely filling a gap in the literature of computational intelligence. The book is built up didactically, the novel results in the field being presented in the way of starting with two real-life case studies, one in the area of waste management, while the other one in modelling bank management systems. In both cases, the book starts with explaining the applied problem and then presenting how the model construction is done and what problems emerge when attempts are made for applying directly earlier results on FCM modelling. In the first case study, the problem of the oversimplification leads to inadequacy of the model, and then it is shown how new, much finer models can be built up based on expert domain knowledge. Then, the new problem of losing transparency and interpretability emerges, and as a solution, a new algorithm family is proposed that reduces FCMs to fewer components, while preserving the essential characteristics of the original model.The second case study raises the problems of stability and sensitivity of FCMs, especially, considering that expert knowledge is often uncertain and subjective. The new results summarised in the book target the questions of how to ascertain whether an FCM is converging to one or several fixed point attractors, whether there is a bifurcation when parameters are changing, etc. Both problems deal with the ultimate question whether the system modelled is stable and sustainable.
Fuzzy Computing in Data Science: Applications and Challenges (Smart and Sustainable Intelligent Systems)
by Sachi Nandan Mohanty Prasenjit Chatterjee Bui Thanh HungFUZZY COMPUTING IN DATA SCIENCE This book comprehensively explains how to use various fuzzy-based models to solve real-time industrial challenges. The book provides information about fundamental aspects of the field and explores the myriad applications of fuzzy logic techniques and methods. It presents basic conceptual considerations and case studies of applications of fuzzy computation. It covers the fundamental concepts and techniques for system modeling, information processing, intelligent system design, decision analysis, statistical analysis, pattern recognition, automated learning, system control, and identification. The book also discusses the combination of fuzzy computation techniques with other computational intelligence approaches such as neural and evolutionary computation. Audience Researchers and students in computer science, artificial intelligence, machine learning, big data analytics, and information and communication technology.
Fuzzy Control and Identification
by John H. LillyThis book gives an introduction to basic fuzzy logic and Mamdani and Takagi-Sugeno fuzzy systems. The text shows how these can be used to control complex nonlinear engineering systems, while also also suggesting several approaches to modeling of complex engineering systems with unknown models.Finally, fuzzy modeling and control methods are combined in the book, to create adaptive fuzzy controllers, ending with an example of an obstacle-avoidance controller for an autonomous vehicle using modus ponendo tollens logic.
Fuzzy Control in Environmental Engineering
by Wojciech Z. ChmielowskiThis book is intended for engineers, technicians and people who plan to use fuzzy control in more or less developed and advanced control systems for manufacturing processes, or directly for executive equipment. Assuming that the reader possesses elementary knowledge regarding fuzzy sets and fuzzy control, by way of a reminder, the first parts of the book contain a reminder of the theoretical foundations as well as a description of the tools to be found in the Matlab/Simulink environment in the form of a toolbox. The major part of the book presents applications for fuzzy controllers in control systems for various manufacturing and engineering processes. It presents seven processes and problems which have been programmed using fuzzy controllers. The issues discussed concern the field of Environmental Engineering. Examples are the control of a flood wave passing through a hypothetical, and then the real Dobczyce reservoir in the Raba River, which is located in the upper Vistula River basin in Southern Poland, the control and water management in a cascade of reservoirs, a broadly defined combustion process model, modern water heating systems and many other.
Fuzzy Controller Design: Theory and Applications (Automation and Control Engineering)
by Zdenko Kovacic Stjepan BogdanFuzzy control methods are critical for meeting the demands of complex nonlinear systems. They bestow robust, adaptive, and self-correcting character to complex systems that demand high stability and functionality beyond the capabilities of traditional methods. A thorough treatise on the theory of fuzzy logic control is out of place on the design bench. That is why Fuzzy Controller Design: Theory and Applications offers laboratory- and industry-tested algorithms, techniques, and formulations of real-world problems for immediate implementation. With surgical precision, the authors carefully select the fundamental elements of fuzzy logic control theory necessary to formulate effective and efficient designs. The book supplies a springboard of knowledge, punctuated with examples worked out in MATLAB®/SIMULINK®, from which newcomers to the field can dive directly into applications. It systematically covers the design of hybrid, adaptive, and self-learning fuzzy control structures along with strategies for fuzzy controller design suitable for on-line and off-line operation. Examples occupy an entire chapter, with a section devoted to the simulation of an electro-hydraulic servo system. The final chapter explores industrial applications with emphasis on techniques for fuzzy controller implementation and different implementation platforms for various applications.With proven methods based on more than a decade of experience, Fuzzy Controller Design: Theory and Applications is a concise guide to the methodology, design steps, and formulations for effective control solutions.
Fuzzy Decision Analysis: Multi Attribute Decision Making Approach (Studies in Computational Intelligence #1121)
by Farhad Hosseinzadeh Lotfi Somayeh Razipour GhalehJough Tofigh Allahviranloo Witold Pedrycz Mohammadreza Shahriari Hamid SharafiAuthored by a leading expert in the field, this book introduces an innovative methodology that harnesses the power of fuzzy logic to enhance decision-making in multi-attribute scenarios. In a world of complexity and uncertainty, effective decision-making is paramount. Springer proudly presents a cutting-edge publication that revolutionizes decision analysis: "Fuzzy Decision Analysis: Multi-attribute Decision-Making Approach." This book stands at the forefront of decision analysis, introducing the integration of fuzzy logic into multi-attribute decision-making. It is a transformative journey into the realm of advanced decision analysis. It book not only equips you with the knowledge to comprehend the theoretical underpinnings but also empowers you to apply these insights in practical scenarios. This book serves as your indispensable companion. Its comprehensive coverage serves as a beacon, guiding you through the intricate maze of fuzzy logic and multi-attribute decision-making, ultimately empowering you to embrace innovation and master the art of making well-informed decisions in an ever-changing world.
Fuzzy Differential Equations and Applications for Engineers and Scientists
by Diptiranjan Behera S. Chakraverty Smita TapaswiniDifferential equations play a vital role in the modeling of physical and engineering problems, such as those in solid and fluid mechanics, viscoelasticity, biology, physics, and many other areas. In general, the parameters, variables and initial conditions within a model are considered as being defined exactly. In reality there may be only vague, imprecise or incomplete information about the variables and parameters available. This can result from errors in measurement, observation, or experimental data; application of different operating conditions; or maintenance induced errors. To overcome uncertainties or lack of precision, one can use a fuzzy environment in parameters, variables and initial conditions in place of exact (fixed) ones, by turning general differential equations into Fuzzy Differential Equations ("FDEs"). In real applications it can be complicated to obtain exact solution of fuzzy differential equations due to complexities in fuzzy arithmetic, creating the need for use of reliable and efficient numerical techniques in the solution of fuzzy differential equations. These include fuzzy ordinary and partial, fuzzy linear and nonlinear, and fuzzy arbitrary order differential equations. This unique work?provides a new direction for the reader in the use of basic concepts of fuzzy differential equations, solutions and its applications. It can serve as an essential reference work for students, scholars, practitioners, researchers and academicians in engineering and science who need to model uncertain physical problems.
Fuzzy Dynamic Equations, Dynamic Inclusions, and Optimal Control Problems on Time Scales
by Svetlin G. GeorgievThe theory of dynamic equations has many interesting applications in control theory, mathematical economics, mathematical biology, engineering and technology. In some cases, there exists uncertainty, ambiguity, or vague factors in such problems, and fuzzy theory and interval analysis are powerful tools for modeling these equations on time scales. The aim of this book is to present a systematic account of recent developments; describe the current state of the useful theory; show the essential unity achieved in the theory fuzzy dynamic equations, dynamic inclusions and optimal control problems on time scales; and initiate several new extensions to other types of fuzzy dynamic systems and dynamic inclusions. The material is presented in a highly readable, mathematically solid format. Many practical problems are illustrated, displaying a wide variety of solution techniques. The book is primarily intended for senior undergraduate students and beginning graduate students of engineering and science courses. Students in mathematical and physical sciences will find many sections of direct relevance.
Fuzzy Fractional Differential Operators and Equations: Fuzzy Fractional Differential Equations (Studies in Fuzziness and Soft Computing #397)
by Tofigh AllahviranlooThis book contains new and useful materials concerning fuzzy fractional differential and integral operators and their relationship. As the title of the book suggests, the fuzzy subject matter is one of the most important tools discussed. Therefore, it begins by providing a brief but important and new description of fuzzy sets and the computational calculus they require. Fuzzy fractals and fractional operators have a broad range of applications in the engineering, medical and economic sciences. Although these operators have been addressed briefly in previous papers, this book represents the first comprehensive collection of all relevant explanations. Most of the real problems in the biological and engineering sciences involve dynamic models, which are defined by fuzzy fractional operators in the form of fuzzy fractional initial value problems. Another important goal of this book is to solve these systems and analyze their solutions both theoretically and numerically. Given the content covered, the book will benefit all researchers and students in the mathematical and computer sciences, but also the engineering sciences.
Fuzzy Hierarchical Model for Risk Assessment
by Xiaojun Wang Hing Kai ChanRisk management is often complicated by situational uncertainties and the subjective preferences of decision makers. Fuzzy Hierarchical Model for Risk Assessment introduces a fuzzy-based hierarchical approach to solve risk management problems considering both qualitative and quantitative criteria to tackle imprecise information. This approach is illustrated through number of case studies using examples from the food, fashion and electronics sectors to cover a range of applications including supply chain management, green product design and green initiatives. These practical examples explore how this method can be adapted and fine tuned to fit other industries as well. Supported by an extensive literature review, Fuzzy Hierarchical Model for Risk Assessment comprehensively introduces a new method for project managers across all industries as well as researchers in risk management. this area.
Fuzzy Image Processing and Applications with MATLAB
by Tamalika Chaira Ajoy Kumar RayIn contrast to classical image analysis methods that employ "crisp" mathematics, fuzzy set techniques provide an elegant foundation and a set of rich methodologies for diverse image-processing tasks. However, a solid understanding of fuzzy processing requires a firm grasp of essential principles and background knowledge. Fuzzy Image Processing and Applications with MATLAB® presents the integral science and essential mathematics behind this exciting and dynamic branch of image processing, which is becoming increasingly important to applications in areas such as remote sensing, medical imaging, and video surveillance, to name a few. Many texts cover the use of crisp sets, but this book stands apart by exploring the explosion of interest and significant growth in fuzzy set image processing. The distinguished authors clearly lay out theoretical concepts and applications of fuzzy set theory and their impact on areas such as enhancement, segmentation, filtering, edge detection, content-based image retrieval, pattern recognition, and clustering. They describe all components of fuzzy, detailing preprocessing, threshold detection, and match-based segmentation. Minimize Processing Errors Using Dynamic Fuzzy Set Theory This book serves as a primer on MATLAB and demonstrates how to implement it in fuzzy image processing methods. It illustrates how the code can be used to improve calculations that help prevent or deal with imprecision—whether it is in the grey level of the image, geometry of an object, definition of an object’s edges or boundaries, or in knowledge representation, object recognition, or image interpretation. The text addresses these considerations by applying fuzzy set theory to image thresholding, segmentation, edge detection, enhancement, clustering, color retrieval, clustering in pattern recognition, and other image processing operations. Highlighting key ideas, the authors present the experimental results of their own new fuzzy approaches and those suggested by different authors, offering data and insights that will be useful to teachers, scientists, and engineers, among others.
Fuzzy Information and Engineering-2019 (Advances in Intelligent Systems and Computing #1094)
by Bing-Yuan CaoThis book includes 70 selected papers from the Ninth International Conference on Fuzzy Information and Engineering (ICFIE) Satellite, which was held on December 26–30, 2018; and from the 9th International Conference on Fuzzy Information and Engineering (ICFIAE), which was held on February 13–15, 2019. The two conferences presented the latest research in the areas of fuzzy information and engineering, operational research and management, and their applications.
Fuzzy Information Processing 2020: Proceedings of the 2020 Annual Conference of the North American Fuzzy Information Processing Society, NAFIPS 2020 (Advances in Intelligent Systems and Computing #1337)
by Vladik Kreinovich Barnabás Bede Martine Ceberio Martine De CockThis book describes how to use expert knowledge—which is often formulated by using imprecise (fuzzy) words from a natural language. In the 1960s, Zadeh designed special "fuzzy" techniques for such use. In the 1980s, fuzzy techniques started controlling trains, elevators, video cameras, rice cookers, car transmissions, etc. Now, combining fuzzy with neural, genetic, and other intelligent methods leads to new state-of-the-art results: in aerospace industry (from drones to space flights), in mobile robotics, in finances (predicting the value of crypto-currencies), and even in law enforcement (detecting counterfeit banknotes, detecting online child predators and in creating explainable AI systems). The book describes these (and other) applications—as well as foundations and logistics of fuzzy techniques. This book can be recommended to specialists—both in fuzzy and in various application areas—who will learn latest techniques and their applications, and to students interested in innovative ideas.
Fuzzy Information Processing 2023 (Lecture Notes in Networks and Systems #751)
by Kelly Cohen Nicholas Ernest Barnabas Bede Vladik KreinovichThis book is an overview of latest successes and applications of fuzzy techniques—techniques that use expert knowledge formulated by natural-language words like "small". Engineering applications deal with aerospace (control of spacecrafts and unmanned aerial vehicles, air traffic control, airport passenger flow predictions), materials (designing gold nano-structures for medicine, catalysis, and sensors), and robot navigation and manipulation. Other application areas include cosmology, demographics, finances, wine production, medicine (diagnostics, epidemics control), and predicting human behavior. In many cases, fuzzy techniques are combined with machine learning AI. Due to natural-language origin of fuzzy techniques, such combination adds explainability (X) to AI. This book is recommended to students and practitioners interested in the state-of-the-art fuzzy-related XAI and to researchers willing to take on numerous remaining challenges.
Fuzzy Investment Decision Making with Examples
by Cengiz Kahraman Elif HaktanırThis book is a practical and theoretical guide that demonstrates how to leverage investment data in numerical models despite uncertainty and ambiguity. The author presents innovative methods that incorporate fuzzy set theory to overcome the imprecision of expert opinions and appraisals. Through real industry case studies and comparative analyses, the book provides a comprehensive understanding of how these novel approaches can be implemented to measure robustness. This book is a must-read for managers involved in investment decision making, for economists, lecturers, as well as M.Sc. and Ph.D. students studying investment decision-making.
Fuzzy Logic and Hydrological Modeling
by null Zekai SenThe hydrological sciences typically present grey or fuzzy information, making them quite messy and a choice challenge for fuzzy logic application. Providing readers with the first book to cover fuzzy logic modeling as it relates to water science, the author takes an approach that incorporates verbal expert views and other parameters that allow
Fuzzy Logic and Neural Networks for Hybrid Intelligent System Design (Studies in Computational Intelligence #1061)
by Oscar Castillo Patricia MelinThis book covers recent developments on fuzzy logic, neural networks and optimization algorithms, as well as their hybrid combinations. In addition, the above-mentioned methods are applied to areas such as intelligent control and robotics, pattern recognition, medical diagnosis, time series prediction and optimization of complex problems. Nowadays, the main topic of the book is highly relevant, as most current intelligent systems and devices in use utilize some form of intelligent feature to enhance their performance. In addition, on the theoretical side, new and advanced models and algorithms of type-2 and type-3 fuzzy logic are presented, which are of great interest to researchers working on these areas. Also, new nature-inspired optimization algorithms and innovative neural models are put forward in the manuscript, which are very popular subjects, at this moment. There are contributions on theoretical aspects as well as applications, which make the book very appealing to a wide audience, ranging from researchers to professors and graduate students.