

This book constitutes the refereed proceedings of the 9th Dortmund Fuzzy Days, Dortmund, Germany, 2006. This conference has established itself as an international forum for the discussion of new results in the field of Computational Intelligence. The papers presented here, all thoroughly reviewed, are devoted to foundational and practical issues in fuzzy systems, neural networks, evolutionary algorithms, and machine learning and thus cover the whole range of computational intelligence.
A glimpse inside

The book highlights how computational intelligence is inherently interdisciplinary, drawing from computer science, mathematics, engineering, and cognitive science. By bringing together diverse approaches—such as fuzzy logic, neural networks, and evolutionary computation—the field aims to tackle complex, real-world problems that are difficult or impossible to solve with traditional algorithms. This synthesis of methods is a recurring theme, showing how hybrid systems can outperform single-paradigm solutions.
A significant portion of the book is dedicated to fuzzy systems, which model and manage uncertainty and imprecision in data. Unlike classical logic, fuzzy logic allows for degrees of truth, making it especially useful in fields where binary decisions are inadequate. The proceedings include both theoretical advances and practical case studies, demonstrating how fuzzy systems can improve decision-making in areas like control systems, diagnostics, and pattern recognition.
- 1Interdisciplinary Foundations of Computational Intelligence
- 2Fuzzy Systems for Handling Uncertainty
- 3Advances in Neural Networks
- 4Evolutionary Algorithms and Optimization
- 5Machine Learning: Theory and Practice