Evolving Systems

Evolving Systems is published by SPRINGER HEIDELBERG and is in Zone 4 of Computer Science in the CAS Journal Ranking (2025 upgraded edition). By OpenAlex counts of its recent articles, its largest topics are Neural Networks and Applications, Metaheuristic Optimization Algorithms Research and Data Stream Mining Techniques, together about 26.6% of its articles. Its main subfields are Artificial Intelligence. (generated from OpenAlex topic counts and CAS ranking data)

Evolving Systems covers surveys, methodological, and application-oriented papers in the area of dynamically evolving systems addressing continual (life-long) learning, open-set classification, self-learning and self-developing, self-evolving models and 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 primarily focused on parametric optimisation, evolving systems allow the learning representations and the model structure or architecture to gradually change/evolve. The aim of such continuous or life-long learning and domain adaptation is self-organisation. 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 learning and adapting after being designed (at run time). Evolving Systems solicits publications that address the problems of all aspects of system modelling, clustering, classification, prediction, anomaly detection and control in non-stationary, unpredictable environments and describe new methods and approaches for their design. 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. The journal is encompassing contributions related to: 1) Methods of machine learning, AI, computational intelligence and mathematical modelling 2) Inspiration from Nature and Biology, including Neuroscience, Bioinformatics and Molecular biology, Quantum

From the journal's Aims & Scope

Research area (LetPub): COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Editor-in-chief Plamen AngelovPublisher website

Editorial board by country: 3 in mainland China (about 5%); most named Italy 9, Brazil 9, United Kingdom 8, Mainland China 3, United States 3 (56 members with a country) Editorial board ↗Publisher website · 2026-09-29

CAS Journal Ranking

Database indexing

SCIEScopusLetPub

International journal early-warning lists: not listed in any editionLetPub

Indexing the journal's website claims

EI CompendexINSPECCASDBLPCurrent ContentsPublisher website

Other: Google Scholar, EBSCO, ProQuest, Dimensions, CNKI, Baidu, ACM Digital Library, Naver, OCLC, Portico, CLOCKSS

As the journal's website lists them, not checked against each database; for Web of Science editions the records above apply.

Editions, and major and minor categories, are shown separately and never merged into one zone; check which edition your institution uses before you submit or report.

Impact

Impact factor

3.68LetPub · 2026-09-13

Impact factor (publisher) 2025

3.7Publisher website · 2026-09-29

5-year impact factor (publisher) 2025

3.4Publisher website · 2026-09-29

CiteScore 2026-06

8.1LetPub · 2026-09-13

SJR 2026-06

0.75LetPub · 2026-09-13

SNIP 2026-06

1.19LetPub · 2026-09-13

h-index

52OpenAlex · 2026-10-01

i10-index

326OpenAlex · 2026-10-01

2-year mean citedness

4.15OpenAlex · 2026-10-01

Self-citation rate

5.4%LetPub · 2026-09-13

Share of gold OA articles

8.42%LetPub · 2026-09-13

Volume

Articles per year

125LetPub · 2026-09-13

Downloads per year (publisher) 2025

115,300Publisher website · 2026-09-29

Sources count differently and were observed at different times, so each source's own value is kept; "publisher" marks figures from the journal's website.

Other sources

Submission to first decision

26 daysPublisher website · 2026-09-29

Peer review

Double anonymous peer reviewPublisher website

Community reports come from authors' own submissions (confidence 0.5) and are not a promise from the journal; for publisher figures, the journal's own definitions apply.

A hybrid journal charges the APC only when the author chooses open access; publishing under the subscription model is usually free.

The journal's website is authoritative for fees; sources were observed at different times and each keeps its own value, without averaging.

Excerpts are quoted from the journal's website; "model summary" lines are written by Workers AI and checked against the text. The journal's website is authoritative.

Publisher

SPRINGER HEIDELBERG

Country or region

GERMANY

Language

English

Frequency

6 issues per year

ISSN

1868-6478

Electronic ISSN

1868-6486

Official links

• Journal homepage ↗OpenAlex
• Submission system ↗LetPub
• Author guidelines ↗LetPub
• Special issues ↗Publisher website