Evolving SystemsSCIE

英文簡介Evolving Systems期刊介紹

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.

期刊簡介Evolving Systems期刊介紹

《Evolving Systems》是一本計算機科學優(yōu)秀雜志。致力于發(fā)表原創(chuàng)科學研究結(jié)果，并為計算機科學各個領(lǐng)域的原創(chuàng)研究提供一個展示平臺，以促進計算機科學領(lǐng)域的的進步。該刊鼓勵先進的、清晰的闡述，從廣泛的視角提供當前感興趣的研究主題的新見解，或?qū)彶槎嗄陙砟硞€重要領(lǐng)域的所有重要發(fā)展。該期刊特色在于及時報道計算機科學領(lǐng)域的最新進展和新發(fā)現(xiàn)新突破等。該刊近一年未被列入預警期刊名單，目前已被權(quán)威數(shù)據(jù)庫SCIE收錄，得到了廣泛的認可。

該期刊投稿重要關(guān)注點：

• 預計審稿時間：
• 計算機科學
• COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
• SCIE
• 中科院4區(qū)
• 非預警