الصفحة 1
الصفحة 1
Neuro–Fuzzy Associative Machinery for Comprehensive Brain and Cognition Modelling
Neuro–Fuzzy Associative Machinery for Comprehensive Brain and Cognition Modelling" is a graduate–level monographic textbook. It represents a comprehensive introduction into both conceptual and rigorous brain and cognition modelling. It is devoted to understanding, prediction and control of the fundamental mechanisms of brain functioning. The reader will be provided with a scientific tool enabling him to perform a competitive research in brain and cognition modelling.
Neural Networks in a Softcomputing Framework
This concise but comprehensive textbook provides a powerful and universal paradigm for information processing. Each chapter provides state-of-the-art descriptions of the important major research results of the respective neural-network methods. A range of relevant computational intelligence topics, such as fuzzy logic and evolutionary algorithms, are introduced. These are powerful tools for neural-network learning. Array signal processing problems are discussed in order to illustrate the applications of each neural-network model.
Multi-Objective Machine Learning
This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems.
Modeling and Management of Fuzzy Semantic RDF Data
Presents the latest research findings in fuzzy RDF data modeling and management. Fuzziness widely exist in many data and knowledge intensive applications. With the increasing amount of metadata available, efficient and scalable management of massive semantic data with uncertainty is of crucial importance. This book goes to great depth concerning the fast-growing topic of technologies and approaches of modeling and managing fuzzy metadata with Resource Description Framework (RDF) format. Its major topics include representation of fuzzy RDF data, fuzzy RDF graph matching, query of fuzzy RDF data, and persistence of fuzzy RDF data in diverse databases. The objective of the book is to provide the state-of-the-art information to researchers, practitioners, and postgraduates students who work on the area of big data intelligence and at the same time serve as the uncertain data and knowledge engineering professional as a valuable real-world reference.
Intelligent Mobile Robot Navigation
the book spans across different domains ranging from mobile robots to intelligent transportation systems, from automatic control to artificial intelligence.
Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing : An Evolutionary Approach for Neural Networks and Fuzzy Systems
This monograph describes new methods for intelligent pattern recognition using soft computing techniques including neural networks, fuzzy logic, and genetic algorithms. Hybrid intelligent systems that combine several soft computing techniques are needed due to the complexity of pattern recognition problems.
Fuzzy Systems Engineering : Theory and Practice
This book is devoted to reporting innovative and significant progress in fuzzy system engineering. Given the maturation of fuzzy logic, this book is dedicated to exploring the recent breakthroughs in fuzziness and soft computing in favour of intelligent system engineering. This monograph presents novel developments of the fuzzy theory as well as interesting applications of the fuzzy logic exploiting the theory to engineer intelligent systems.
Fuzzy systems and knowledge discovery ; Vol. 4223 ; Third International Conference, FSKD 2006, Xi'an, China, September 24-28, 2006, Proceedings
ICNC-FSKD 2006 featured the most up-to-date research results in com- tational algorithms inspired from nature, including biological, ecological, and physical systems. It is an exciting and emerging interdisciplinary area in which a wide rangeof techniques and methods arebeing studied for dealing with large, complex, and dynamic problems.
Fuzzy systems and knowledge discovery ; Vol. 3614 ; 2nd International Conference, FSKD 2005, Changsha, China, August 27-29, 2005, Proceedings, Part II
This book and its sister volume, LNAI 3613 and 3614, constitute the proce- ings of the Second International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2005), jointly held with the First International Conference on Natural Computation (ICNC 2005, LNCS 3610, 3611, and 3612) from - gust 27–29, 2005 in Changsha, Hunan, China. FSKD 2005 successfully attracted 1249 submissions from 32 countries/regions (the joint ICNC-FSKD 2005 received 3136 submissions). After rigorous reviews, 333 high-quality papers, i. e. , 206 long papers and 127 short papers, were included in the FSKD 2005 proceedings, r- resenting an acceptance rate of 26. 7%. The ICNC-FSKD 2005 conference featured the most up-to-date research - sults in computational algorithms inspired from nature, including biological, e- logical, and physical systems. It is an exciting and emerging interdisciplinary area in which a wide range of techniques and methods are being studied for dealing with large, complex, and dynamic problems. The joint conferences also promoted cross-fertilization over these exciting and yet closely-related areas, which had a signi?cant impact on the advancement of these important technologies. Speci?c areas included computation with words, fuzzy computation, granular com- tation, neural computation, quantum computation, evolutionary computation, DNA computation, chemical computation, information processing in cells and tissues, molecular computation, arti?cial life, swarm intelligence, ants colony, arti?cial immune systems, etc. , with innovative applications to knowledge d- covery, ?nance, operations research, and more.
Fuzzy systems and knowledge discovery ; Vol. 3613 ; 2nd International Conference, FSKD 2005, Changsha, China, August 27-29, 2005, Proceedings, Part I
This book and its sister volume, LNAI 3613 and 3614, constitute the proce- ings of the Second International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2005), jointly held with the First International Conference on Natural Computation (ICNC 2005, LNCS 3610, 3611, and 3612) from - gust 27–29, 2005 in Changsha, Hunan, China. FSKD 2005 successfully attracted 1249 submissions from 32 countries/regions (the joint ICNC-FSKD 2005 received 3136 submissions). After rigorous reviews, 333 high-quality papers, i. e. , 206 long papers and 127 short papers, were included in the FSKD 2005 proceedings, r- resenting an acceptance rate of 26. 7%. The ICNC-FSKD 2005 conference featured the most up-to-date research - sults in computational algorithms inspired from nature, including biological, e- logical, and physical systems. It is an exciting and emerging interdisciplinary area in which a wide range of techniques and methods are being studied for dealing with large, complex, and dynamic problems. The joint conferences also promoted cross-fertilization over these exciting and yet closely-related areas, which had a signi?cant impact on the advancement of these important technologies. Speci?c areas included computation with words, fuzzy computation, granular com- tation, neural computation, quantum computation, evolutionary computation, DNA computation, chemical computation, information processing in cells and tissues, molecular computation, arti?cial life, swarm intelligence, ants colony, arti?cial immune systems, etc. , with innovative applications to knowledge d- covery, ?nance, operations research, and more.
Fuzzy portfolio optimization : Theory and methods
This is the first monograph on fuzzy portfolio optimization. By using fuzzy mathematical approaches, quantitative analysis, qualitative analysis, the experts' knowledge and the investors' subjective opinions can be better integrated into portfolio selection models. The contents of this book mainly comprise of the authors' research results for fuzzy portfolio selection problems in recent years. In addition, in the book, the authors introduce some other important progress in the field of fuzzy portfolio optimization. Some fundamental issues and problems of portfolio selection have been studied systematically and extensively by the authors to apply fuzzy systems theory and optimization methods. A new framework for investment analysis is presented in this book. A series of portfolio selection models are given and some of them are more efficient for practical applications. Some application examples are given to illustrate those models.
Fuzzy Logic and Applications ; Vol. 3849 ; 6th International Workshop, WILF 2005, Crema, Italy, September 15-17, 2005, Revised Selected Papers
This volume contains the proceedings of the 6th International Workshop on Soft Computing and Applications (WILF 2005), which took place in Crema, Italy, on September 15–17, 2005, continuing an established tradition of biannual meetings among researchers and developers from both academia and industry to report on the latest scienti?c and theoretical advances, to discuss and debate major issues, and to demonstrate state-of-the-art systems. This edition of the workshop included two special sessions, sort of subwo- shops, focusing on the application of soft computing techniques (or compu- tional intelligence) to image processing (SCIP) and bioinformatics (CIBB).
Fuzzy Logic and Applications ; Vol. 2955 ; 5th International Workshop, WILF 2003, Naples, Italy, October 9-11, 2003, Revised Selected Papers
This volume constitutes the thoroughly refereed post-workshop proceedings of the 5th International Workshop on Fuzzy Logic and Applications held in Naples, Italy, in October 2003. The 40 revised full papers presented have gone through two rounds of reviewing and revision. All current issues of theoretical, experimental and applied fuzzy logic and related techniques are addressed with special attention to rough set theory, neural networks, genetic algorithms and soft computing.
Fuzzy Control and Filter Design for Uncertain Fuzzy Systems
ThisbookpresentsnewnovelmethodologiesfordesigningrobustH fuzzy ? controllers and robustH fuzzy ?lters for a class of uncertain fuzzy systems ? (UFSs), uncertain fuzzy Markovian jump systems (UFMJSs), uncertain fuzzy singularly perturbed systems (UFSPSs) and uncertain fuzzy singularly p- turbed systems with Markovian jumps (UFSPS–MJs). These new meth- ologies provide a framework for designing robustH fuzzy controllers and ? robustH fuzzy ?lters for these classes of systems based on a Tagaki-Sugeno ? (TS) fuzzy model. Solutions to the design problems are presented in terms of linear matrix inequalities (LMIs).
Fuzzy Control : Fundamentals, Stability and Design of Fuzzy Controllers
The book provides a critical discussion of fuzzy controllers from the perspective of classical control theory. Special emphases are placed on topics that are of importance for industrial applications, like (self-) tuning of fuzzy controllers, optimisation and stability analysis. The book is written as a textbook for graduate students as well as a comprehensive reference book about fuzzy control for researchers and application engineers. Starting with a detailed introduction to fuzzy systems and control theory the reader is guided to up-to-date research results.
Fuzzy Chaotic Systems : Modeling, Control, and Applications
"Fuzzy Chaotic Systems" provides original heuristic research achievements and insightful ideas on the interactions or intrinsic relationships between fuzzy logic and chaos theory. It presents the fundamental concepts of fuzzy logic and fuzzy control, chaos theory and chaos control, as well as thedefinition of chaos on the metric space of fuzzy sets. This monograph discusses and illustrates fuzzy modeling and fuzzy control of chaotic systems, synchronization, anti-control of chaos, intelligent digital redesign, spatiotemporal chaos and synchronization in complex fuzzy systems; as well as a practical application example of fuzzy-chaos-based cryptography. Like other very good books, this book may raise more questions than it can provide answers. It therefore generates a great potential to attract more attention to combine fuzzy systems with chaos theory and contains important seeds for future scientific research and engineering applications.
Fundamentals of the New Artificial Intelligence: Neural, Evolutionary, Fuzzy and More
The significantly updated second edition of Fundamentals of the New Artificial Intelligence thoroughly covers the most essential and widely employed material pertaining to neural networks, genetic algorithms, fuzzy systems, rough sets, and chaos. In particular, this unique textbook explores the importance of this content for real-world applications.
Foundations of fuzzy logic and soft computing ; 12th International Fuzzy Systems Association World Congress, IFSA 2007, Cancun, Mexico, Junw 18-21, 2007, Proceedings
This book comprises a selection of papers from IFSA 2007 on new methods and theories that contribute to the foundations of fuzzy logic and soft computing. methodologies. Soft computing consists of several computing paradigms which can be used to produce powerful intelligent systems for solving real-world problems.
Engineering Evolutionary Intelligent Systems
This edited volume 'Engineering Evolutionary Intelligent Systems' deals with the theoretical and methodological aspects, as well as various evolutionary algorithm applications to many real world problems originating from science, technology, business or commerce.
Differential Evolution Algorithm with Type-2 Fuzzy Logic for Dynamic Parameter Adaptation with Application to Intelligent Control
This book focuses on the fields of fuzzy logic, bio-inspired algorithm, especially the differential evolution algorithm and also considering the fuzzy control area. The main idea is that these two areas together can help solve various control problems and to find better results. In this book, the authors test the proposed method using five benchmark control problems. First, the water tank, temperature, mobile robot, and inverted pendulum controllers are considered. For these 4 problems, experimentation was carried out using a Type-1 fuzzy system and an Interval Type-2 system. The last control problem was the D.C. motor, for which the experiments were performed with Type-1, Interval Type-2, and Generalized Type-2 fuzzy systems. When we use fuzzy systems combined with the differential evolution algorithm, we can notice that the results obtained in each of the controllers are better and with increasing uncertainty, the results are even better. For this reason, the authors consider in this book the proposed method using fuzzy systems and the differential evolution algorithm to improve the fuzzy controllers’ behavior in complex control problems.
