© 2016

Engineering Applications of Neural Networks

17th International Conference, EANN 2016, Aberdeen, UK, September 2-5, 2016, Proceedings

  • Chrisina Jayne
  • Lazaros Iliadis
Conference proceedings EANN 2016

Part of the Communications in Computer and Information Science book series (CCIS, volume 629)

Table of contents

  1. Front Matter
    Pages I-XI
  2. Active Learning and Dynamic Environments

    1. Front Matter
      Pages 1-1
    2. Ahmed Hussein, Mohamed Medhat Gaber, Eyad Elyan
      Pages 3-17
    3. G. L. Masala, B. Golosio, M. Tistarelli, E. Grosso
      Pages 18-34
    4. Joana Costa, Catarina Silva, Mário Antunes, Bernardete Ribeiro
      Pages 35-47
  3. Semi-supervised Modeling

    1. Front Matter
      Pages 49-49
    2. Ilias Bougoudis, Konstantinos Demertzis, Lazaros Iliadis, Vardis-Dimitris Anezakis, Antonios Papaleonidas
      Pages 51-63
  4. Classification Applications

    1. Front Matter
      Pages 65-65
    2. Ariel Ruiz-Garcia, Mark Elshaw, Abdulrahman Altahhan, Vasile Palade
      Pages 79-93
    3. Hana Schaabova, Vladimir Krajca, Vaclava Sedlmajerova, Olena Bukhtaieva, Lenka Lhotska, Jitka Mohylova et al.
      Pages 94-107
  5. Clustering Applications

  6. Cyber-Physical Systems and Cloud Applications

    1. Front Matter
      Pages 159-159
    2. Andrei Petrovski, Prapa Rattadilok, Sergey Petrovskii
      Pages 161-175
    3. Catalina Hernández, Sergio Villagrán, Paulo Gaona
      Pages 176-185
    4. Ioannis M. Stephanakis, Syed Noor-Ul-Hassan Shirazi, Antonios Gouglidis, David Hutchison
      Pages 186-197

About these proceedings


This book constitutes the refereed proceedings of the 17th International Conference on Engineering Applications of Neural Networks, EANN 2016, held in Aberdeen, UK, in September 2016.

The 22 revised full papers and three short papers presented together with two tutorials were carefully reviewed and selected from 41 submissions. The papers are organized in topical sections on active learning and dynamic environments; semi-supervised modeling; classification applications; clustering applications; cyber-physical systems and cloud applications; time-series prediction; learning-algorithms.


algorithms artificial intelligence classification models clustering computational intelligence deep learning learning algorithms machine learning neural networks pattern recognition signal processing speech recognition supervised learning Support Vector Machines (SVM)

Editors and affiliations

  • Chrisina Jayne
    • 1
  • Lazaros Iliadis
    • 2
  1. 1.Robert Gordon UniversityAberdeenUnited Kingdom
  2. 2.Lab of Forest Informatics (FiLAB)Democritus University of Thrace Lab of Forest Informatics (FiLAB)OrestiadaGreece

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