Buch, Englisch, 296 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 699 g
Buch, Englisch, 296 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 699 g
Reihe: Studies in Fuzziness and Soft Computing
ISBN: 978-3-540-25006-7
Verlag: Springer Berlin Heidelberg
Computational Intelligence (CI) has emerged as a novel and highly diversified paradigm supporting the design, analysis and deployment of intelligent systems. This book presents a careful selection of the field that very well reflects the breadth of the discipline. It covers a range of highly relevant and practical design principles governing the development of intelligent systems in data mining, robotics, bioinformatics, and intelligent tutoring systems. The lucid presentations, coherent organization, breadth and the authoritative coverage of the area make the book highly attractive for everybody interested in the design and analysis of intelligent systems.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Technische Wissenschaften Technik Allgemein Computeranwendungen in der Technik
- Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
- Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
- Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computer-Aided Design (CAD)
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
- Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
Weitere Infos & Material
Part I: NZ – German School of Computational Intelligence at KES2004.- Basics of Engineering The Intelligent Hybrid Systems - Not Industrial Applications Only.- Basics of Machine Learning by Support Vector Machines.- Supporting Deep Learning in an Open-ended Domain.- Data Driven Fuzzy Modelling with Neural Networks.- Hybrid Computational Intelligence Systems for Real World Applications.- Autonomous Intelligent Systems – from Sci-Fi to Reality.- Part II - Selected KES2004 Conference Tutorials.- Introduction to Rough Set Theory and Applications.- Bioinformatics with Evolutionary Computation.- Data Mining; Algorithms and Applications.
