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Engineering - Computational Intelligence and Complexity | Evolving Systems - incl. option to publish open access (Editorial Board)

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Evolving Systems

Evolving Systems

An Interdisciplinary Journal for Advanced Science and Technology

Editors-in-Chief: P. Angelov; D. Filev; N.K. Kasabov

ISSN: 1868-6478 (print version)
ISSN: 1868-6486 (electronic version)

Journal no. 12530

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Dr Plamen Angelov, Lancaster University, UK


Dr Dimitar Filev, Ford Motor Company, USA

Professor Nikola Kasabov, Auckland University of Technology, New Zealand

Associate Editors

  • Agapito Ismael Ledezma, University Carlos III, Spain
  • Daniel Leite, Federal University of Lavras, Brasil
  • Valeri Mladenov, Technical University of Sofia, Bulgaria
  • Mahardhika Pratama, Nanyang Technological University, Singapore
  • Leszek Rutkowski, Institute of Computational Intelligence; Poland
  • Teck Hou Teng, Singapore Management University, Singapore

Advisory Board:

  • Abdoulhamid Bouchachia, Bournemouth University, UK
  • Janusz Kacprzyk, Polish Academy of Sciences, Poland
  • Rudolf Kruse, Otto-von-Guericke-Universität Magdeburg, Germany
  • Chin Teng Lin, National Chiao-Tung University, Hsinchu, Taiwan
  • Witold Pedrycz, University of Alberta, Canada
  • Tomohiro Takagi, Meiji University, Tokyo, Japan
  • Ronald Yager, Machine Intelligence Institute, Iona College, NY, USA

Editorial Board:

  • Cesare Alippi, Politecnico di Milano, Italy
  • Bruno Costa, IFRN, Natal, Brazil
  • Fernando Gomide, UNICAMP, Brazil
  • Rong Haijun, Jiaotong University, China
  • Jose Antonio Iglesias Martínez, Universidad Carlos III de Madrid, Spain
  • Lazaros Iliadis, Democritos University of Thrace, Greece
  • Er Meng Joo, Nanyang Technological University, Singapore
  • Dmitry Kangin, University of Exeter, UK
  • Trevor Martin, University of Bristol, UK
  • Moamar Sayed Mouchaweh, Ecole de Mines, Douai, France
  • Seiichi Ozawa, Osaka University, Japan
  • Andre Paim Lemos, Federal University of Minas Gerais, Brasil
  • Seiichi Ozawa, Kobe University, Japan
  • Radu Emil Precup, University of Timisoara, Romania
  • Pouria Sadeghi-Tehran, Rothamsted Research, UK
  • Olga Senyukova, Lomonosov Moscow State University, Russia
  • Igor Škrjanc, University of Ljubljana, Slovenia
  • Suresh Sundaram, Nanyang Technological University, Singapore
  • Marley Vellasco, Pontificial Catholic University of Rio de Janeiro, Brazil
  • Di Wang, Khalifa University, UAE
  • Wilson Wang, Lakeland University, Canada
  • M J Watts, Auckland Institute of Studies, New Zealand.

Read this Journal on Springerlink

For authors and editors

  • Aims and Scope

    Aims and Scope


    "Evolving Systems" covers surveys, methodological, and application-oriented papers in the emerging area of evolving systems. Evolving systems are inspired by the idea of system model evolution in a dynamically changing and evolving environment. They use inheritance and gradual change with the aim of life-long learning and adaptation, self-organization including system structure evolution in order to adapt to the (unknown and unpredictable) environment as structures for information representation with the ability to fully adapt their structure and adjust their parameters.

    "Evolving Systems" solicits publications that address the problems of modelling, control, prediction, classification and data processing in non-stationary, unpredictable environments and describe new methods and approaches for design of systems able to fully adapt its structure rather than adjust its parameters based on a pre-trained and fixed structure.

    The journal is devoted to the topic of self-developing, self-organised, and evolving systems in its entirety - from systematic methods to case studies and real industrial applications. It covers all aspects of the methodology such as

    • conventional systems,
    • neuro-fuzzy systems,
    • evolutionary systems,
    • Bayesian systems,
    • machine learning methods,
    • clustering, and
    • classification,

    but also looking at new paradigms and applications, including medicine, robotics, business, industrial automation, control systems, transportation, communications, environmental monitoring, biomedical systems, security, and electronic services. The common features for all submitted methods and systems are evolvability and knowledge discovery.

    The journal is encompassing contributions related to: 

    1) Methods of computational intelligence and mathematical modelling 

    2) Inspiration from Nature and Biology, including Neuroscience, Bioinformatics and Molecular biology, Quantum physics

    3) Applications in engineering, business, social sciences. 

  • Submit Online
  • Open Choice - Your Way to Open Access
  • Instructions for Authors

    Instructions for authors


  • CFP Applications of Evolving Connectioni...
  • CFP Temporal Aspects in Fuzzy Cognitive ...
  • CFP Adaptive and on-line learning in non...
  • Forthcoming Conference EAIS 2014
  • Author Academy: Training for Authors
  • English Language Editing

    English Language Editing


  • CfP - Data Stream Mining (pdf, 421 kB)
  • CfP Evolving Sensor Systems (pdf, 413 kB...
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