Evolving Systems

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).

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.

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 physics

3) Applications in engineering, business, social sciences.

《Evolving Systems》是一本由SPRINGER HEIDELBERG出版商出版的专业计算机科学期刊，刊期6 issues per year，该刊已被国际权威数据库SCI、SCIE收录。在中科院最新升级版分区表中，该刊分区信息为大类学科：计算机科学4区，小类学科：计算机：人工智能 4区；在JCR（Journal Citation Reports）分区等级为Q3。该刊发文范围涵盖计算机人工智能等领域，旨在及时、准确、全面地报道国内外计算机人工智能工作者在该领域取得的最新研究成果、工作进展及学术动态、技术革新等，促进学术交流，鼓励学术创新。2022年影响因子为3.2，