期刊全称 | Evolving Systems | |||||||||||||||||||||||||||||||||||||||||||||
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涉及主题
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期刊介绍 | 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. | |||||||||||||||||||||||||||||||||||||||||||||
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期刊ISSN | print: 1868-6478on-line: 1868-6486 | |||||||||||||||||||||||||||||||||||||||||||||
2023最新影响因子 (2024年6月20日公布) 与上一年的差值 |
2.7↓ 0.5 | |||||||||||||||||||||||||||||||||||||||||||||
历年影响因子 |
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历年发表/被引量 (科研通AI通过大数据分析) 最后更新日期:2025-04-27 |
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h-index(2021) | 暂无h-index数据 | |||||||||||||||||||||||||||||||||||||||||||||
自引率 | 7.40% | |||||||||||||||||||||||||||||||||||||||||||||
涉及的研究领域 | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE- | |||||||||||||||||||||||||||||||||||||||||||||
中科院2025年分区 (2025年3月20日发布) |
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WOS期刊分区 (2024年6月20日公布) |
JCR学科分类
JCI学科分类
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中科院SCI期刊分区 (2023年12月升级版) |
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中科院SCI期刊分区 (2022年12月升级版) |
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中科院SCI期刊分区 (2021年12月基础版) |
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中科院SCI期刊分区 (2021年12月升级版) |
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中科院《国际期刊预警名单(试行)》名单 |
2024年02月发布的2024版:不在预警名单中 2023年01月发布的2023版:不在预警名单中 2021年12月发布的2021版:不在预警名单中 2021年01月发布的2020版:不在预警名单中 |
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期刊主页 |
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投稿网址 | https://www.editorialmanager.com/evos/ | |||||||||||||||||||||||||||||||||||||||||||||
编辑部地址 | TIERGARTENSTRASSE 17, HEIDELBERG, GERMANY, D-69121 | |||||||||||||||||||||||||||||||||||||||||||||
出版商 | SPRINGER HEIDELBERG | |||||||||||||||||||||||||||||||||||||||||||||
出版国家(地区) | GERMANY | |||||||||||||||||||||||||||||||||||||||||||||
出版语言 | English | |||||||||||||||||||||||||||||||||||||||||||||
出版周期 | 6 issues per year | |||||||||||||||||||||||||||||||||||||||||||||
每年出版文章数 | 71 | |||||||||||||||||||||||||||||||||||||||||||||
Gold OA文章占比 | 5.48% | |||||||||||||||||||||||||||||||||||||||||||||
原创研究文献占比 (排除综述) |
93.24% | |||||||||||||||||||||||||||||||||||||||||||||
SCI收录类型 |
Science Citation Index Expanded (SCIE) Scopus (CiteScore) |
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PubMed链接 | http://www.ncbi.nlm.nih.gov/nlmcatalog?term=1868-6478%5BISSN%5D | |||||||||||||||||||||||||||||||||||||||||||||
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平均录用比例 | 网友分享经验: |
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