Intelligent Data Engineering and Automated Learning - IDEAL 2015

16th International Conference, Wroclaw, Poland, October 14-16, 2015, Proceedings
1. Auflage 2015
ISBN: 978-3-319-24833-2
Verlag: Springer International Publishing

Buch, Englisch, 560 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 8657 g

Reihe: Information Systems and Applications, incl. Internet/Web, and HCI

This book constitutes the refereed proceedings of the
16th International Conference on Intelligent Data Engineering and Automated
Learning, IDEAL 2015, held in Wroclaw, Poland, in October 2015.

The 64 revised full papers presented were carefully
reviewed and selected from 127 submissions. These papers provided a valuable
collection of recent research outcomes in data engineering and automated
learning, from methodologies, frameworks, and techniques to applications. In
addition to various topics such as evolutionary algorithms, neural networks,
probabilistic modeling, swarm intelligent, multi-objective optimization, and
practical applications in regression, classification, clustering, biological
data processing, text processing, video analysis, IDEAL 2015 also featured a
number of special sessions on several emerging topics such as computational
intelligence for optimization of communication networks, discovering knowledge
fromdata, simulation-driven DES-like modeling and performance evaluation, and
intelligent applications in real-world problems.

Zielgruppe

Research

Autoren/Hrsg.

Jackowski, Konrad

Burduk, Robert

Yin, Hujun

Walkowiak, Krzysztof

Wozniak, Michal

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen

Inhaltsverzeichnis

Evolutionary algorithms.- Neural networks.- Probabilistic modeling.- Swarm intelligent, multi-objective optimization, and practical applications in regression.- Classification.- Clustering.-Biological data processing.- Text processing.- Video analysis.- Computational intelligence for optimization of communication networks.- Discovering knowledge from data.- Simulation-driven DES-like modeling and performance evaluation.- Intelligent applications in real-world problems.