Intelligent Data Engineering and Automated Learning ¿ IDEAL 2017

Hujun Yin

ISBN 10: 3319689347 / ISBN 13: 9783319689340

Published by Springer International Publishing Okt 2017, 2017

About this Item

This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed proceedings of the 18th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2017, held in Guilin, China, in October/November 2017.The 65 full papers presented were carefully reviewed and selected from 110 submissions. These papers provided a sample of latest research outcomes in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, deep learning neural networks, probabilistic modelling, particle swarm intelligence, big data analytics, and applications in image recognition, regression, classification, clustering, medical and biological modelling and prediction, text processing and social media analysis. 628 pp. Englisch.

Seller Inventory # 9783319689340

Bibliographic Details

• Title: Intelligent Data Engineering and Automated Learning ¿ IDEAL 2017
• Publisher: Springer International Publishing Okt 2017
• Publication Date: 2017
• Language: English
• ISBN 10: 3319689347
• ISBN 13: 9783319689340
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 34D millimeters 235 millimeters width by 155 millimeters height by 34 millimeters depth
• Weight: 937 grams

About this title

Synopsis

This book constitutes the refereed proceedings of the 18th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2017, held in Guilin, China, in October/November 2017.

The 65 full papers presented were carefully reviewed and selected from 110 submissions. These papers provided a sample of latest research outcomes in data engineering and automated learning, from methodologies, frameworks and techniques to applications. In addition to various topics such as evolutionary algorithms, deep learning neural networks, probabilistic modelling, particle swarm intelligence, big data analytics, and applications in image recognition, regression, classification, clustering, medical and biological modelling and prediction, text processing and social media analysis.