The textbook offers a comprehensive introduction to intelligent systems, emphasizing fundamental concepts and practical implementations. The enhanced third edition includes updated content on deep learning, scalarization methods, large-scale optimization algorithms, and collective decision-making algorithms, making it a valuable resource for understanding intelligent behavior in complex environments.
This book provides a critical discussion of fuzzy controllers from the perspective of classical control theory. The text begins with a detailed introduction to fuzzy systems and control theory, and guides the reader to a thorough understanding of up-to-date research results.
In recent years there has been a growing interest to extend classical methods for data analysis. The aim is to allow a more flexible modeling of phenomena such as uncertainty, imprecision or ignorance. Such extensions of classical probability theory and statistics are useful in many real-life situations, since uncertainties in data are not only present in the form of randomness --- various types of incomplete or subjective information have to be handled. About twelve years ago the idea of strengthening the dialogue between the various research communities in the field of data analysis was born and resulted in the International Conference Series on Soft Methods in Probability and Statistics (SMPS). This book gathers contributions presented at the SMPS'2012 held in Konstanz, Germany. Its aim is to present recent results illustrating new trends in intelligent data analysis. It gives a comprehensive overview of current research into the fusion of soft computing methods with probability and statistics. Synergies of both fields might improve intelligent data analysis methods in terms of robustness to noise and applicability to larger datasets, while being able to efficiently obtain understandable solutions of real-world problems.
A rigorous explanation of fuzzy systems theory plus a detailed illustration of specific practical applications of the powerful engineering tool they represent. Contains a discussion of cutting-edge technology supplemented by the analysis of several successful applications in the areas of approximate reasoning, fuzzy control and fuzzy analysis. Includes scores of exercises, problems, worked examples, step-by-step solutions and comprehensive references.
Prof. Dr. Rudolf Kruse und Dr. Jörg Gebhardt arbeiten am Institut für Betriebssysteme und Rechnerverbund der TU Braunschweig. Dr. Rainer Palm ist in der Zentralabteilung Forschung und Entwicklung der Siemens AG München tätig.
This clearly-structured, classroom-tested textbook/reference presents a methodical introduction to the field of CI. Providing an authoritative insight into all that is necessary for the successful application of CI methods, the book describes fundamental concepts and their practical implementations, and explains the theoretical background underpinning proposed solutions to common problems. Only a basic knowledge of mathematics is required. Features: provides electronic supplementary material at an associated website, including module descriptions, lecture slides, exercises with solutions, and software tools; contains numerous examples and definitions throughout the text; presents self-contained discussions on artificial neural networks, evolutionary algorithms, fuzzy systems and Bayesian networks; covers the latest approaches, including ant colony optimization and probabilistic graphical models; written by a team of highly-regarded experts in CI, with extensive experience in both academia and industry.