Intelligent Data Engineering and Automated Learning ¿ IDEAL 2016

Hujun Yin

ISBN 10: 3319462563 / ISBN 13: 9783319462561

Published by Springer International Publishing Sep 2016, 2016

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed proceedings of the 17 International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2016, held in Yangzhou, China, in October 2016. The 68 full papers presented were carefully reviewed and selected from 115 submissions. They provide a valuable and timely sample of latest research outcomes in data engineering and automated learning ranging from methodologies, frameworks, and techniques to applications including various topics such as evolutionary algorithms; deep learning; neural networks; probabilistic modeling; particle swarm intelligence; big data analysis; applications in regression, classification, clustering, medical and biological modeling and predication; text processing and image analysis. 664 pp. Englisch.

Seller Inventory # 9783319462561

Bibliographic Details

• Title: Intelligent Data Engineering and Automated Learning ¿ IDEAL 2016
• Publisher: Springer International Publishing Sep 2016
• Publication Date: 2016
• Language: English
• ISBN 10: 3319462563
• ISBN 13: 9783319462561
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 36D millimeters 235 millimeters width by 155 millimeters height by 36 millimeters depth
• Weight: 990 grams

About this title

Synopsis

This book constitutes the refereed proceedings of the 17 International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2016, held in Yangzhou, China, in October 2016.

The 68 full papers presented were carefully reviewed and selected from 115 submissions. They provide a valuable and timely sample of latest research outcomes in data engineering and automated learning ranging from methodologies, frameworks, and techniques to applications including various topics such as evolutionary algorithms; deep learning; neural networks; probabilistic modeling; particle swarm intelligence; big data analysis; applications in regression, classification, clustering, medical and biological modeling and predication; text processing and image analysis.