Intelligent Data Engineering and Automated Learning – IDEAL 2016

17th International Conference, Yangzhou, China, October 12–14, 2016, Proceedings

  • Hujun Yin
  • Yang Gao
  • Bin Li
  • Daoqiang Zhang
  • Ming Yang
  • Yun Li
  • Frank Klawonn
  • Antonio J. Tallón-Ballesteros
Conference proceedings IDEAL 2016

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9937)

Also part of the Information Systems and Applications, incl. Internet/Web, and HCI book sub series (LNISA, volume 9937)

Table of contents

  1. Front Matter
    Pages I-XVI
  2. Xianfeng Liu, Yamin Zuo
    Pages 1-9
  3. Shuihua Wang, Lenan Wu, Yuankai Huo, Xueyan Wu, Hainan Wang, Yudong Zhang
    Pages 10-17
  4. Zhong-bao Liu, Jing Zhang, Wen-ai Song
    Pages 18-27
  5. Yali Liang, Xiaohua Xu, Zheng Liao, Ping He
    Pages 28-36
  6. Qiang Lu, You Xu, Yixin Chen, Ruoyun Huang, Ling Chen
    Pages 37-45
  7. Jie Ding, Xinshan Zhu
    Pages 79-88
  8. Tiantian Zhang, Bo Yuan
    Pages 89-98
  9. Chenlu Qiu, Huiying Xu, Yongqiang Bao
    Pages 99-105
  10. Qiang-Mei Wu, Wei Liu, Hai-yan Hong, Ling Chen
    Pages 106-113
  11. Zheng Wang, Qingsong Yu, Chaomin Shen, Wenxin Hu
    Pages 134-142
  12. B. Wu, T. H. Yan, X. S. Xu, B. He, W. H. Li
    Pages 164-173
  13. Yang Li, Hang Li, Yulong Xu, Jiabao Wang, Yafei Zhang
    Pages 174-182

About these proceedings


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.



bioinformatics data mining evolutionary data machine learning neural networks applied computing artificial intelligence cloud computing computing methodologies data management systems genetic algorithm health informatics human computer interaction information retrieval internet of things middleware model-checking neural informatics Web applications Web mining

Editors and affiliations

  • Hujun Yin
    • 1
  • Yang Gao
    • 2
  • Bin Li
    • 3
  • Daoqiang Zhang
    • 4
  • Ming Yang
    • 5
  • Yun Li
    • 6
  • Frank Klawonn
    • 7
  • Antonio J. Tallón-Ballesteros
    • 8
  1. 1.University of ManchesterManchesterUnited Kingdom
  2. 2.Nanjing UniversityNanjingChina
  3. 3.Yangzhou UniversityYangzhouChina
  4. 4.Aeronautics and AstronauticsNanjing University Aeronautics and AstronauticsNanjingChina
  5. 5.Nanjing Normal UniversityNanjingChina
  6. 6.Yangzhou UniversityYangzhouChina
  7. 7.Ostfalia University of Applied SciencesWolfenbüttelGermany
  8. 8.University of SevilleSevilleSpain

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing AG 2016
  • Publisher Name Springer, Cham
  • eBook Packages Computer Science
  • Print ISBN 978-3-319-46256-1
  • Online ISBN 978-3-319-46257-8
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • About this book