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

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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Plamen Angelov
Dr Plamen Angelov is a Reader in Computational Intelligence and coordinator of the Intelligent Systems Research at Infolab21, Lancaster University, UK. He is a Senior Member of the IEEE and Chair of the Technical Committee on Evolving Intelligent Systems, Systems, Man and Cybernetics Society, IEEE. He is also a member of the UK Autonomous Systems National TC, of the Autonomous Systems Study Group, NorthWest Science Council, UK and of the Autonomous Systems Network of the Society of British Aerospace Companies. He is also a founding member of the Centre of Excellence in CyberSecurity officially recognised by UK GCHQ for the period 2012-2017.
He authored or co-authored over 160 peer reviewed publications in leading journals (50+) peer-reviewed conference proceedings, a patent, a research monograph, a number of edited books, and has an active research portfolio in the area of computational intelligence and autonomous system modelling, identification, and machine learning. He has internationally recognised pioneering results into on-line and evolving methodologies and algorithms for knowledge extraction in the form of human-intelligible fuzzy rule-based systems and autonomous machine learning.
Dr. Angelov is also a very active researcher leading numerous projects (over a dozen for the last five-six years) funded by UK and EU research councils, industry, HM Government, including UK Ministry of Defence (total funding in order of tens of millions pounds with well over £1M for his group alone). His research contributes to the competitiveness of the industry, defence and quality of life and was recognised by ‘The Engineer Innovation and Technology 2008 Award in two categories: i) Aerospace and Defence and ii) The Special Award.
Dr. Angelov is also the founding Editor-in-Chief of the Springer journal Evolving Systems and serves as an Associate Editor of several other international journals, including IEEE Transactions on Systems, Man and Cybernetics, on Fuzzy Systems, Elsevier’s Fuzzy Sets and Systems, Journal on Automation, Mobile Robotics and Intelligent Systems etc. He also Chairs annual conferences organised by IEEE acts as Visiting Professor (in Brazil, Germany, Spain) regularly gives invited and plenary talks at leading companies and universities More information can be found at Dr Angelov's web site


Filev Dimitar
Dr. Dimitar P. Filev is a Senior Technical Leader - Intelligent Control & Information Systems, Ford Research & Advanced Engineering. He is conducting research in modeling and control of complex systems, intelligent control, fuzzy and neural systems, and their applications to automotive engineering.
He is recipient of the 2008 Norbert Wiener Award of the IEEE SMC Society, the 2007 IFSA Outstanding Industrial Applications Award, and the highest Ford Motor Company corporate awards – he was awarded 5 times with the Henry Ford Technology Award for development and implementation of advanced automotive technologies and he received the 2010 Inaugural Haren Gandhi Research & Innovation Award for his long term research contributions.
He has published 4 books and over 200 articles in refereed journals and conference proceedings, and holds over 40 US and foreign patents. He is past president of NAFIPS and serves presently as VP for Cybernetics of the IEEE SMC Society. Dr. Filev is a Fellow of IEEE and IFSA. He received his PhD. degree in Electrical Engineering from the Czech Technical University in Prague in 1979.


Prof. Nikola Kasabov
Professor Nikola K. Kasabov, Fellow IEEE, Fellow RSNZ, obtained his Masters degree in computing and electrical engineering (1971) and PhD in mathematical sciences (1975) from the Technical University of Sofia, Bulgaria. He is the Director and the Founder of the Knowledge Engineering and Discovery Research Institute (KEDRI, www.kedri.info) and Professor of Knowledge Engineering at the School of Computing and Mathematical Sciences at the Auckland University of Technology. Before that he worked at the technical University of Sofia, University of Essex in the UK, University of Otago.
He has published more than 450 papers, books and patents in the areas of information science, computational intelligence, neural networks, bioinformatics, neuroinformatics. Prof. Kasabov was the President of the International Neural Network Society (INNS) for 2009 and 2010 and now he is a Governor of INNS. He is also a Past President of the Asia Pacific Neural Network Assembly (APNNA). He is a Distinguished IEEE CIS Lecturer (2011-2013). He is an EU Marie Curie Fellow and a Visiting Professor at the Institute for Neuroinformatics of the University of Zurich and ETH (http://ncs.ethz.ch/projects/evospike) and a Guest Professor at the Shanghai Jiao Tong University.
Among his awards are the APPNA Outstanding Achievement Award (2012), the INNS Gabor Award (2012), the AUT VC Individual Research Excellence Award (2010), the Bayer Innovation Award (2007), the APPNA Excellence Award (2005), the RSNZ Science and Technology Medal (2002) and numerous IEEE best paper awards. He has given more than 50 keynote and plenary talks at international conferences and served as a chair and a committee member of numerous IEEE, ICONIP, ANNES and other international conferences. More than 35 PhD students have graduated under his supervision.
Kasabov is Co-Editor–in-Chief of the Springer journal Evolving Systems, Editor of the Springer Handbook of Bio-and Neuroinformatics and series editor of the Springer Series in Bio-/Neuroinformatics.

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  • 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. 

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