الصفحة 3
الصفحة 3
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.
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.
Frontiers of high performance computing and networking – ISPA 2007 workshops ; ISPA 2007 International workshops, SSDSN, UPWN, WISH, SGC, ParDMCom, HiPCoMB, and IST-AWSN, Niagara Falls, Canada, August, 28-September 1, 2007, Proceedings
This book constitutes the refereed joint proceedings of seven international workshops held in conjunction with the 5th International Symposium on Parallel and Distributed Processing and Applications, ISPA 2007, held in Niagara Falls, Canada in August 2007.
Frontiers in Algorithmics ; 2nd Annual International Workshop, FAW 2008, Changsha, China, June 19-21, 2008, Proceeedings
This book constitutes the refereed proceedings of the Second International Frontiers of Algorithmics Workshop, FAW 2008, held in Changsha, China, in June 2008.The 33 revised full papers presented together with the abstracts of 3 invited talks were carefully reviewed and selected from 80 submissions. The papers were selected for 9 special focus tracks in the areas of biomedical informatics, discrete structures, geometric information processing and communication, games and incentive analysis.
Foundations of learning classifier systems
This volume brings together recent theoretical work in Learning Classifier Systems (LCS), which is a Machine Learning technique combining Genetic Algorithms and Reinforcement Learning. It includes self-contained background chapters on related fields (reinforcement learning and evolutionary computation) tailored for a classifier systems audience and written by acknowledged authorities in their area - as well as a relevant historical original work by John Holland.
Foundations of Genetic Algorithms ; 9th International Workshop, FOGA 2007, Mexico City, Mexico, January 8-11, 2007, Revised Selected Papers
Readers will find here a fascinating text that is the thoroughly refereed post-proceedings of the 9th Workshop on the Foundations of Genetic Algorithms, FOGA 2007, held in Mexico City in January 2007.
Foundations of genetic algorithms ; 8th International Workshop, FOGA 2005, Aizu-Wakamatsu City, Japan, January 5-9, 2005, Revised Selected Papers
The8thWorkshopontheFoundationsofGeneticAlgorithms,FOGA-8,washeld at the University of Aizu in Aizu-Wakamatsu City, Japan, January 5–9, 2005. This series of workshops was initiated in 1990 to encourage further research on the theoretical aspects of genetic algorithms, and the workshops have been held biennially ever since. The papers presented at these workshops are revised, edited and published as volumes during the year following each workshop. This series of (now eight) volumes provides an outstanding source of reference for the theoretical work in this ?eld. At the same time this series of volumes provides a clear picture of how the theoretical research has grown and matured along with the ?eld to encompass many evolutionary computation paradigms including evolution strategies (ES), evolutionary programming (EP), and genetic programming (GP), as well as the continuing growthininteractionswith other ?elds suchas mathematics,physics, and biology.
Foundations of generic optimization : Vol.1 : A combinatorial approach to epistasis
This is a comprehensive overview of the basics of fuzzy control, which also brings together some recent research results in soft computing, in particular fuzzy logic using genetic algorithms and neural networks. This book offers researchers not only a solid background but also a snapshot of the current state of the art in this field.
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.
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.
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.
Evolvable systems : From biology to hardware ; 7th International Conference, ICES 2007, Wuhan, China, September 21-23, 2007, Proceedings
The 41 revised full papers collected in this volume are organized in topical sections on digital hardware evolution, analog hardware evolution, bio-inspired systems, mechanical hardware evolution, evolutionary design, evolutionary algorithms in hardware design, and hardware implementation of evolutionary algorithms.
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.
Evolvable Hardware
The contributions in this book provide the basics of reconfigurable devices so that readers will be fully prepared to understand what EHW is, why it is necessary and how it is designed. The book also discusses the leading research in digital, analog and mechanical EHW. Selections from leading international researchers offer examples of cutting-edge research and applications, placing particular emphasis on their practical usefulness.
Evolutionary Synthesis of Pattern Recognition Systems
Evolutionary Synthesis of Pattern Recognition Systems presents novel effective approaches based on evolutionary computational techniques, such as genetic programming (GP), linear genetic programming (LGP), coevolutionary genetic programming (CGP) and genetic algorithms (GA) to automate the synthesis and analysis of object detection and recognition systems. The book’s concepts, principles, and methodologies will enable readers to automatically build robust and flexible systems—in a systematic manner—that can provide human-competitive performance and reduce the cost of designing and maintaining these systems. Its content covers all key aspects of object recognition: object detection, feature selection, feature discovery, object recognition, domain knowledge. Basic knowledge of programming and data structures, and some calculus, is presupposed.ing the book’s novel ideas
Evolutionary Multiobjective Optimization : Theoretical Advances and Applications
Evolutionary Multiobjective Optimization is a rare collection of the latest state-of-the-art theoretical research, design challenges and applications in the field of multiobjective optimization paradigms using evolutionary algorithms. It includes two introductory chapters giving all the fundamental definitions, several complex test functions and a practical problem involving the multiobjective optimization of space structures under static and seismic loading conditions used to illustrate the various multiobjective optimization concepts.
Evolutionary Multi-Criterion Optimization ; 4th International Conference, EMO 2007, Matsushima, Japan, March 5-8, 2007, Proceedings
Multicriterion optimization refers to problems with two or more objectives (normally in conflict with each other) which must be simultaneously satisfied. Evolutionary algorithms have been used for solving multicriterion optimization problems for over two decades, gaining an increasing attention from industry. This book included four keynote speakers: Hirotaka Nakayama on aspiration level methods, Kay Chen Tan on large and computationally intensive real-world MO optimization problems, Carlos Fonseca on decision making, and Gary B. Lamont on design of large-scale network centric systems.
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.
Evolutionary Computer Music
The evolutionary computation approach to music is an exciting new development for composers and musicologists alike. For composers, it provides an innovative and natural means for generating musical ideas from a specifiable set of primitive components and processes. For musicologists, these techniques are used to model the cultural transmission and change of a population's body of musical ideas over time. In both cases, musical evolution can be guided by a variety of constraints and tendencies built into the system, such as realistic psychological factors that influence the way music is expressed, experienced, learned, stored, modified, and passed on among individuals. This book discusses not only the applications of evolutionary computation to music, but also the tools needed to create and study such systems. These tools are drawn in part from research into the origins and evolution of biological organisms, ecologies, and cultural systems on the one hand, and from computer simulation methodologies on the other. They can be combined to create surrogate artificial worlds populated by interacting simulated organisms in which complex musical experiments can be performed that would otherwise be impossible.
Evolutionary computation, machine learning and data mining in bioinformatics ; 6th European Conference, EvoBIO 2008, Naples, Italy, March 26-28, 2008. Proceedings
The feld of bioinformatics has two main objectives: the creation and main- nance of biological databases, and the discovery of knowledge from life sciences data in order to unravel the mysteries of biological function, leading to new drugs and therapies for human disease. Life sciences data come in the form of biological sequences, structures, pathways, or literature. One major aspect of discovering biological knowledge is to search, predict, or model specifc infortioninagivendatasetinorderto generate new in teresting knowledge.Computer science methods such as evolutionary computation, machine learning, and data mining all have a great deal to ofer the feld of bioinformatics.
