Evolving Systems

Journal Title

Evolving Systems

EVOL SYST-GER

ISSN / eISSN

1868-6478 / 1868-6486

Aims and Scope

Evolving Systems covers surveys, methodological, and application-oriented papers in the area of dynamically evolving systems. ‘Evolving systems’ are inspired by the idea of system model evolution in a dynamically changing and evolving environment. In contrast to the standard approach in machine learning, mathematical modelling and related disciplines where the model structure is assumed and fixed a priori and the problem is focused on parametric optimisation, evolving systems allow the model structure to gradually change/evolve. The aim of such continuous or life-long learning and domain adaptation is self-organization. It can adapt to new data patterns, is more suitable for streaming data, transfer learning and can recognise and learn from unknown and unpredictable data patterns. Such properties are critically important for autonomous, robotic systems that continue to learn and adapt after they are being designed (at run time).<br />
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Evolving Systems solicits publications that address the problems of all aspects of system modelling, clustering, classification, prediction and control in non-stationary, unpredictable environments and describe new methods and approaches for their design.<br />
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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


Evolving Systems methodology
Evolving Neural Networks and Neuro-fuzzy Systems
Evolving Classifiers and Clustering
Evolving Controllers and Predictive models
Evolving Explainable AI systems
Evolving Systems applications


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, finance and economics. The common features for all submitted methods and systems are the evolving nature of the systems and the environments.<br />
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The journal is encompassing contributions related to: <br />
1) Methods of machine learning, AI, computational intelligence and mathematical modelling <br />
2) Inspiration from Nature and Biology, including Neuroscience, Bioinformatics and Molecular biology, Quantum physics<br />
3) Applications in engineering, business, social sciences.

Subject Area

COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

CiteScore

7.80 View Trend

CiteScore Ranking

Category	Quartile	Rank
Mathematics - Control and Optimization	Q1	#10/130
Mathematics - Modeling and Simulation	Q1	#25/324
Mathematics - Control and Systems Engineering	Q1	#57/321
Mathematics - Computer Science Applications	Q1	#167/817

Web of Science Core Collection

Science Citation Index Expanded (SCIE)	Social Sciences Citation Index (SSCI)
Indexed	-

Category (Journal Citation Reports 2024)	Quartile
COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE	Q3

Country/Area of Publication

GERMANY

Publisher

SPRINGER HEIDELBERG

Publication Frequency

6 issues per year

Annual Article Volume

74

Open Access

NO

Contact

TIERGARTENSTRASSE 17, HEIDELBERG, GERMANY, D-69121