Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration

Häftad, Engelska, 2005

Av Earl Cox, NC) Cox, Earl (Scianta Intelligence, LLC, Chapel Hill

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Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers involved in developing data mining models in business and government. As you’ll discover, fuzzy systems are extraordinarily valuable tools for representing and manipulating all kinds of data, and genetic algorithms and evolutionary programming techniques drawn from biology provide the most effective means for designing and tuning these systems.You don’t need a background in fuzzy modeling or genetic algorithms to benefit, for this book provides it, along with detailed instruction in methods that you can immediately put to work in your own projects. The author provides many diverse examples and also an extended example in which evolutionary strategies are used to create a complex scheduling system.

Produktinformation

Utgivningsdatum2005-02-24
Mått184 x 259 x undefined mm
Vikt1 110 g
FormatHäftad
SpråkEngelska
SerieMorgan Kaufmann Series in Data Management Systems
Antal sidor540
FörlagElsevier Science & Technology
ISBN9780121942755

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Artificiell intelligens inom Data och it
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Earl founded and serves as President of, Scianta Intelligence, a next generation machine intelligence and knowledge exploration company. He is a futurist, author, management consultant, and educator involved in discovering the epistemology of advanced intelligent systems, the redefinition of the machine mind, and, as a pioneer of Internet-based technologies, the way in which evolving inter-connected virtual worlds will affect the sociology of business and culture in the near and far future.Earl has over thirty years experience in managing and participating in the software development process at the system as well as tightly integrated application level. In the area of advanced machine intelligence technologies, Earl is a recognized expert in fuzzy logic, and adaptive fuzzy systems as they are applied to information and decision theory. He has pioneered the integration of fuzzy neural systems with genetic algorithms and case-based reasoning. As an industry observer and futurist, Earl has written and talked extensively on the philosophy of the Response to Change, the nature of Emergent Intelligence, and the Meaning of Information Entropy in Mind and Machine.

PrefaceAcknowledgementsIntroductionPART ONE – CONCEPTS AND ISSUESChapter 1. Foundations and IdeasChapter 2. Principal Model TypesChapter 3. Approaches to Model BuildingPART TWO – FUZZY SYSTEMSChapter 4. Fundamental Concepts of Fuzzy LogicChapter 5. Fundamental Concepts of Fuzzy SystemsChapter 6. FuzzySQL and Intelligent QueriesChapter 7. Fuzzy ClusteringChapter 8. Fuzzy Rule InductionPART THREE – EVOLUTIONARY STRATEGIESChapter 9. Fundamental Concepts of Genetic AlgorithmsChapter 10. Genetic Resource Scheduling OptimizationChapter 11. Genetic Tuning of Fuzzy Models