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Advances in Computational Intelligence Systems

Contributions Presented at the 21st UK Workshop on Computational Intelligence, September 7-9, 2022, Sheffield, UK

  • Conference proceedings
  • © 2024

Overview

Editors:
  1. George Panoutsos

    1. Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, UK

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  2. Mahdi Mahfouf

    1. Department of Automatic Control and Systems Engineering, Head of the Intelligent Systems Research Laboratory, The University of Sheffield, Sheffield, UK

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  3. Lyudmila S Mihaylova

    1. Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, UK

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  • Presents recent research on computational intelligence systems
  • Covers a wide range of application areas
  • Collects the edited contributions presented at the 21st UK Workshop on Computational Intelligence

Part of the book series: Advances in Intelligent Systems and Computing (AISC, volume 1454)

Included in the following conference series:

Conference proceedings info: UKCI 2022.

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About this book

The scope of this book is to present the papers included at the 21st UK Workshop on Computational Intelligence (UKCI 2022), hosted by The University of Sheffield, between 7 and 9 September 2022, Sheffield, UK. This marks the first fully in-person UKCI conference, following the pandemic, a testament to the success and resilience of the UKCI community, as well as to the importance of computational intelligence (CI) research. The papers in this book are divided into five sections: fuzzy logic systems, machine learning, hybrid methods and network systems, deep learning and neural networks, and optimization and search.

Keywords

Table of contents (48 papers)

  1. Front Matter

    Pages i-xi
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  2. Fuzzy Logic Systems

    1. Front Matter

      Pages 1-1
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    2. Mixture Kernel-Based Fuzzy-Rough Feature Selection

      • Xiangxin Song, Guanli Yue, Neil Mac Parthaláin, Yanpeng Qu
      Pages 3-12

    3. Fuzzy Hidden Markov Chain Based Models for Time-Series Data

      • Yihui Tao, Mahdi Mahfouf
      Pages 13-23

    4. No Explanation Without (Fuzzy) Representation

      • Trevor Martin
      Pages 24-36

    5. Noisy Instance Removal Using OWA-Based Fuzzy-Rough Sets

      • Richard Jensen, Neil Mac Parthaláin, Mehran Amiri, Jörg Cassens
      Pages 37-48

    6. A Fuzzy Prescreening Tool to Assist in the Diagnosis of High Functioning Individuals on the Autism Spectrum Who Present with Mental Health Comorbidities

      • Philip Smith, Sarah Greenfield
      Pages 49-60

    7. A Fuzzy Logic-Based Framework for Statistical Process Control in Additive Manufacturing

      • Atakan Sahin, Pilar Rey, George Panoutsos
      Pages 61-72

    8. Towards Dynamic Fuzzy Rule Interpolation with Harmony Search

      • Jinle Lin, Changjing Shang, Qiang Shen
      Pages 73-88

    9. Fuzzy Inference for Well Log Lithology Classification

      • Sam Fetherstonhaugh, John Martin, Tim Pearce, Neil Mac Parthalain, Otar Akanyeti
      Pages 89-102

  3. Machine Learning

    1. Front Matter

      Pages 103-103
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    2. Laplacian Regularized Variational Few-Shot Learning for Image Classification

      • Yumna Zahid, Muhammad Atif Tahir, Jungong Han, Qiang Shen
      Pages 105-116

    3. Modified Probabilistic Neural Networks LBP Classification Based on Distance Measures in Probability Space

      • Shadi Al Amoudi, Xia Hong, Hong Wei
      Pages 117-128

    4. Preliminary Introduction and Implementation of Novel Machine Learning Algorithm Utilising Pareto Principle: Classification of Small Biomedical Health-Related Datasets

      • Ahsanullah Yunas Mahmoud
      Pages 129-141

    5. Nonlinear Model Combination Approach to Decentralised and Privacy-Preserving Classification

      • Mona Alkhozae, Xiao-Jun Zeng
      Pages 142-157

    6. Classification of Imbalanced Immunotherapy and Health-Related Data Utilising Novel Machine Learning Experiments

      • Ahsanullah Yunas Mahmoud
      Pages 158-169

    7. Automatic Scoring of Chair Sit-to-Stand Test Using a Smartphone

      • Arshad Sher, David Langford, Federico Villagra, Otar Akanyeti
      Pages 170-180

    8. Weight Management Programme: Use of Machine Learning Approaches to Identify Client Outcomes

      • Jackie Campbell, Anna Palczewska, Ayotomide Adeyeye, Osayande Omobude, Windi Marva, Claire Griffiths et al.
      Pages 181-191

    9. Injury Risk Prediction in Rugby League Players with Training Volume Data and Machine Learning

      • Christopher Todd, Anna Palczewska, Dan Weaving
      Pages 192-203

    10. Predicting Modified Rankin Scale Scores of Ischemic Stroke Patients Using Radiomics Features and Machine Learning

      • Meryem Åžahin ErdoÄŸan, Esra Sümer, Federico Villagra, Esin Öztürk Işık, Otar Akanyeti, Hale Saybaşılı
      Pages 204-213
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Other volumes

  1. Advances in Computational Intelligence Systems

Editors and Affiliations

  • Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, UK

    George Panoutsos, Lyudmila S Mihaylova

  • Department of Automatic Control and Systems Engineering, Head of the Intelligent Systems Research Laboratory, The University of Sheffield, Sheffield, UK

    Mahdi Mahfouf

Bibliographic Information

  • Book Title: Advances in Computational Intelligence Systems

  • Book Subtitle: Contributions Presented at the 21st UK Workshop on Computational Intelligence, September 7-9, 2022, Sheffield, UK

  • Editors: George Panoutsos, Mahdi Mahfouf, Lyudmila S Mihaylova

  • Series Title: Advances in Intelligent Systems and Computing

  • DOI: https://doi.org/10.1007/978-3-031-55568-8

  • Publisher: Springer Cham

  • eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2024

  • Softcover ISBN: 978-3-031-55567-1Published: 19 May 2024

  • eBook ISBN: 978-3-031-55568-8Published: 18 May 2024

  • Series ISSN: 2194-5357

  • Series E-ISSN: 2194-5365

  • Edition Number: 1

  • Number of Pages: XI, 591

  • Number of Illustrations: 53 b/w illustrations, 141 illustrations in colour

  • Topics: Computational Intelligence, Artificial Intelligence

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