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Forging New Frontiers : Fuzzy Pioneers I

The 2005 BISC International Special Event-BISCSE’05 " FORGING THE FRONTIERS" was held in the University of California, Berkeley, “WHERE FUZZY LOGIC BEGAN, from November 3 – 6, 2005. The successful applications of fuzzy logic and it’s rapid growth suggest that the impact of fuzzy logic will be felt increasingly in coming years. Fuzzy logic is likely to play an especially important role in science and engineering, but eventually its influence may extend much farther. In many ways, fuzzy logic represents a significant paradigm shift in the aims of computing - a shift which reflects the fact that the human mind, unlike present day computers, possesses a remarkable ability to store and process information which is pervasively imprecise, uncertain and lacking in categoricity.

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Flexible Databases Supporting Imprecision and Uncertainty

This volume collects selected contributions on the application of heterogeneous methods for managing uncertainty and imprecision in databases. It contains both survey chapters on classic topics such as "flexible querying in databases", and up to date ontributions on "database models to represent imperfect data". Further, it includes specific contributions on uncertainty management in database integration, and in representing and querying semistructured and spatial data. These topics are of particular relevance nowadays with the diffusion of the internet since, most of the time, applications require information spread across several information sources and their integration may result in inconsistent information.

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First course on fuzzy theory and applications

This basic textbook gives an easily accessible introduction to Fuzzy theory and its applications. It provides basic and concrete concepts of the field in a self-contained, condensed and understandable style. This "First Course on Fuzzy Theory and Applications" includes numerous examples, descriptive illustrations and figures of the basic concepts, as well as exercises at the end of each chapter. The author has long time experience in teaching on fuzzy theory and its applications and continuously developed and summarized his didactic lecture notes into this book. This book can be used in introductory graduate and undergraduate courses in Fuzziness and Soft Computing and is recommendable to students, scientists, engineers, or professionals in the field for self-study.

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Feature Extraction : Foundations and Applications

This book is both a reference for engineers and scientists and a teaching resource, featuring tutorial chapters and research papers on feature extraction. "This book compiles some very promising techniques, coming from an extremely smart collection of researchers, delivering their best ideas in a competitive environment."

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Fault-Diagnosis Systems : An Introduction from Fault Detection to Fault Tolerance

This book gives an introduction into the field of fault detection, fault diagnosis and fault-tolerant systems with methods which have proven their performance in practical applications. It guides the reader in a structured tutorial style: supervision methods, reliability, safety, system integrity and related terminology; fault detection with signal-based methods for periodic and stochastic signals; fault detection with process model-based methods like parameter estimation, state estimation, parity equations and principal component analysis; fault diagnosis with classification and inference methods; fault-tolerant systems with hardware and analytical redundancy; many practical simulation examples and experimental results for processes like electrical motors, pumps, actuators, sensors and automotive components; end-of-chapter exercises for self testing or for practice.

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Evolving Connectionist Systems : The Knowledge Engineering Approach

Evolving Connectionist Systems is aimed at all those interested in developing and using intelligent computational models and systems to solve challenging real world problems in computer science, engineering, bioinformatics and neuroinformatics. The book challenges scientists and practitioners with open questions about future creation of new information models inspired by Nature. This edition includes new methods for adaptive, knowledge-based learning, such as online incremental feature selection, spiking neural networks, transductive neuro-fuzzy inference, adaptive data and model integration, cellular automata and artificial life systems, particle swarm optimisation, ensembles of evolving systems, and quantum inspired neural networks. New applications to gene and protein interaction modelling, brain data analysis and brain model creation, computational neuro-genetic modelling, adaptive speech, image and multimodal recognition, language modelling, adaptive robotics, modelling dynamic financial and socio-economic systems, and ecological modelling, are covered. An important new feature of the book is the attempt to connect different structural and functional levels of a complex, intelligent system, looking for inspiration from functional relationships in natural systems, such as the genetic and the brain activity.

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Evolvable Machines : Theory & Practice

Methods for the artificial evolution of active components, such as programs and hardware, are rapidly developing branches of adaptive computation and adaptive engineering. "Evolvable Machines" reports innovative and significant progress in automatic and evolutionary methodology applied to machine design. This book presents theoretical as well as practical chapters concentrating on Evolvable Robots, Evolvable Hardware Synthesis, as well as Evolvable Design.

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Evolutionary Scheduling

Evolutionary scheduling is a vital research domain at the interface of two important sciences - artificial intelligence and operational research. Scheduling problems are generally complex, large scale, constrained, and multi-objective in nature, and classical operational research techniques are often inadequate at solving them effectively. With the advent of computation intelligence, there is renewed interest in solving scheduling problems using evolutionary computational techniques. These techniques, which include genetic algorithms, genetic programming, evolutionary strategies, memetic algorithms, particle swarm optimization, ant colony systems, etc, are derived from biologically inspired concepts and are well-suited to solve scheduling problems since they are highly scalable and flexible in terms of handling constraints and multiple objectives. This edited book gives an overview of many of the current developments in the large and growing field of evolutionary scheduling, and demonstrates the applicability of evolutionary computational techniques to solve scheduling problems, not only to small-scale test problems, but also fully-fledged real-world problems.

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Evolutionary Multi-Criterion Optimization ; 3rd International Conference, EMO 2005, Guanajuato, Mexico, March 9-11, 2005, Proceedings

Constitutes the refereed proceedings of the Third International Conference on Evolutionary Multi-Criterion Optimization, EMO 2005, held in Guanajuato, Mexico, in March 2005.

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Evolutionary Computation in Practice

This book is loaded with examples in which computer scientists and engineers have used evolutionary computation—programs that mimic natural evolution—to solve real problems. They aren’t abstract, mathematically intensive papers, but accounts of solving important problems, including tips from the authors on how to avoid common pitfalls, maximize the effectiveness and efficiency of the search process, and many other practical suggestions.

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Evolution, Monitoring and Predicting Models of Rockburst : Precursor Information for Rock Failure

Focuses on investigating predicting precursor information and key points of rockburst in mining engineering through laboratory experiment, theoretical analysis, numerical simulation and case studies. Understanding the evolution patterns for the microstructure instability of rock is a prerequisite for rockburst prediction. The book provides a guide for readers seeking to understand the evolution patterns for the microstrucure of rock failure, the predicting key point of rock failure and the rockburst predicting model. It will be an essential reference to understand mechanism of rockburst and sheds new light on dynamic disasters prediction. Chapters are carefully developed to cover (1) The evolution patterns for the microstructure instability of rock; (2) Rockburst hazard monitoring and predicting criterion and predicting models. The book addresses the issue with a holistic and systematic approach that investigates the occurrence mechanism of rockburst based on the evolution patterns for the microstructure of rock failure and establishes the predicting model of rockburst.

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Enhanced Methods in Computer Security, Biometric and Artificial Intelligence Systems

"Methods of Artificial Intelligence and Intelligent Agents" contains 13 contributions analyzing such areas of AI as fuzzy set theory, predicate logic, neural networks, clustering, data mining and others. It also presents applications of AI as possible solutions for problems like firm bankruptcy, soil erosion, flight control and others. "Information Technology Security" covers three important areas of security engineering in information systems: software security, public key infrastructure and the design of new cryptographic protocols and algorithms. "Biometric Systems" comprises 11 contributions dealing with face picture analysis and recognition systems. This chapter focuses on known methods of biometric problem solution as well as the design of new models.

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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.

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Ecological Informatics : Scope, Techniques and Applications

Ecological Informatics promotes interdisciplinary research between ecology and computer science on elucidation of principles of information processing in ecosystems, ecological sustainability by informed decision making, and bio-inspired computation. The 2nd edition of the book consolidates the scope, concepts, and techniques of this newly emerging discipline by a new preface and additional chapters on cellular automata, qualitative reasoning, hybrid evolutionary algorithms and artificial neural networks. It illustrates numerous applications of Ecological Informatics for aquatic and terrestrial ecosystems, image recognition at micro- and macro-scale as well as computer hardware design.

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Do Smart Adaptive Systems Exist? : Best Practice for Selection and Combination of Intelligent Methods

This book is intended as a reference and a guide summarising and focusing on best practices when using intelligent techniques and building systems requiring a degree of adaptation and intelligence. Another attractive feature of the book is that it brings together experts from neural network, fuzzy, machine learning, evolutionary and hybrid systems communities who will provide their views on how these different intelligent technologies have contributed and will contribute to creation of smart adaptive systems of the future.

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DNA Computing ; Vol. 4287 ; 12th International Meeting on DNA Computing, DNA12, Seoul, Korea, June 5-9, 2006, Revised Selected Papers

This book constitutes the thoroughly refereed postproceedings of the 12th International Meeting on DNA Computing, DNA12, held in Seoul, Korea in June 2006. The 34 revised full papers presented are organized in topical sections on molecular and membrane computing models, complexity analysis, sequence and tile designs and their properties, DNA tile self-assembly models, simulator and software for DNA computing, DNA computing algorithms and new applications, novel experimental approaches, and experimental solutions.

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Discrete Optimization with Interval Data : Minmax Regret and Fuzzy Approach

This book is a valuable source of information for all operations research practitioners who are interested in modern approaches to problem solving. Apart from the description of the theoretical framework, it also presents some algorithms that can be applied to solve problems that arise in practice.

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Digital Human Modeling ; 1st International Conference, ICDHM 2007, Held as Part of HCI International 2007, Beijing, China, July 22-27, 2007, Proceedings

Theis book includes human aspects of design and use of computing systems.It covers the entire field of Human-Computer Interaction, addressing major - vances in knowledge and effective use of computers in a variety of application areas. It also contains thematic area of Digital Human Modeling, Shape and Movement Modeling and Anthropometry, Building and Applying Virtual Humans, Medical and Rehabilitation Applications, Industrial and Ergonomic Applications

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Digital Human Modeling : Trends in Human Algorithms

The emerging information technologies have given rise to new human patterns in terms of both physiological and psychological interactions. Human Algorithms aim to model human forms, interactions, and dynamics in this new context.

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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.

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