Part I: Computational Intelligence for the Masses. Computational vs. Artificial Intelligence -- A Roadmap Through the Computational Intelligence Maze -- Fuzzy Systems: Let's Get Fuzzy -- Machine Learning: The Ghost in the Learning Machine -- Evolutionary Computation: The Profitable Gene -- Swarm Intelligence: The Benefits of the Swarms -- Intelligent Agents: The Computer Intelligence Agency (CIA) --- Part II: Computational Intelligence Creates Value. Why We Need Intelligent Solutions? -- Competitive Advantages of Computational Intelligence -- Issues in Applying Computational Intelligence --- Part III: Computational Intelligence Application Strategy: Integrate & Conquer. How to Apply Computational Intelligence? -- Computational Intelligence Marketing -- Examples of Computational Intelligence Industrial Applications --- Part IV: The Future of Applied Computational Intelligence. Future Directions of Applied Computational Intelligence
Summary:
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.
This resource is supported by the Institute of Museum and Library Services under the provisions of the Library Services and Technology Act as administered by State Library of Iowa.