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Applying Computational Intelligence

by Kordon, Arthur.
Authors: SpringerLink (Online service) Physical details: XXII, 459p. 20 illus. online resource. ISBN: 3540699139 Subject(s): Engineering. | Data mining. | Artificial intelligence. | Engineering design. | Technology. | Engineering. | Computational Intelligence. | Technology Management. | Data Mining and Knowledge Discovery. | Artificial Intelligence (incl. Robotics). | Engineering Design.
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E-Book E-Book AUM Main Library 006.3 (Browse Shelf) Not for loan

Computational Intelligence in a Nutshell -- Artificial vs. Computational Intelligence -- A Roadmap Through the Computational Intelligence Maze -- Let's Get Fuzzy -- Machine Learning: The Ghost in the Learning Machine -- Evolutionary Computation: The Profitable Gene -- Swarm Intelligence: The Benefits of Swarms -- Intelligent Agents: The Computer Intelligence Agency (CIA) -- Computational Intelligence Creates Value -- Why We Need Intelligent Solutions -- Competitive Advantages of Computational Intelligence -- Issues in Applying Computational Intelligence -- Computational Intelligence Application Strategy -- Integrate and Conquer -- How to Apply Computational Intelligence -- Computational Intelligence Marketing -- Industrial Applications of Computational Intelligence -- The Future of Computational Intelligence -- Future Directions of Applied Computational Intelligence.

The flow of academic ideas in the area of computational intelligence is impacting industrial practice at considerable speed. Practitioners face the challenge of tracking, understanding and applying the latest techniques, which often prove their value even before the underlying theories are fully understood. This book offers realistic guidelines on creating value from the application of computational intelligence methods. In Part I, the author offers simple explanations of the key computational intelligence technologies: fuzzy logic, neural networks, support vector machines, evolutionary computation, swarm intelligence, and intelligent agents. In Part II, he defines the typical business environment and analyzes the competitive advantages these techniques offer. In Part III, he introduces a methodology for effective real-world application of computational intelligence while minimizing development cost, and he outlines the critical, underestimated technology marketing efforts required. The methodology can improve the existing capabilities of Six Sigma, one of the most popular work processes in industry. Finally, in Part IV the author looks to technologies still in the research domain, such as perception-based computing, artificial immune systems, and systems with evolved structure, and he examines the future for computational intelligence applications while taking into account projected industrial needs. The author adopts a light tone in the book, visualizes many of the techniques and ideas, and supports the text with notes from successful implementations. The book is ideal for engineers implementing these techniques in the real world, managers charged with creating value and reducing costs in the related industries, and scientists in computational intelligence looking towards the application of their research.

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