Evolving Systems
短名 | Evol. Syst. |
Journal Impact | 2.58 |
国际分区 | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE(Q3) |
期刊索引 | SCI Q3中科院 4 区 |
ISSN | 1868-6478, 1868-6486 |
h-index | 35 |
国内分区 | 计算机科学(4区)计算机科学计算机人工智能(4区) |
演化系统涵盖动态演化系统领域的调查、方法论和面向应用的论文。 “进化系统”的灵感来自于系统模型在动态变化和进化的环境中进化的想法。与机器学习、数学建模和相关学科的标准方法相比,其中模型结构是先验假设和固定的,问题集中在参数优化上,进化系统允许模型结构逐渐改变/进化。这种持续或终身学习和领域适应的目的是自组织。它可以适应新的数据模式,更适合流数据、迁移学习,并且可以识别和学习未知和不可预测的数据模式。这些属性对于在设计后(在运行时)继续学习和适应的自主机器人系统至关重要。EVOLVING SYSTEMS 征集解决系统建模、聚类、分类、预测和控制等各个方面问题的出版物。非平稳、不可预测的环境,并描述其设计的新方法和方法。该杂志致力于从系统方法到案例研究和实际工业应用的整个自开发、自组织和演化系统的主题。它涵盖了方法论的所有方面,例如进化系统方法论进化神经网络和神经模糊系统进化分类器和聚类进化控制器和预测模型进化可解释的人工智能系统进化系统应用程序,但也着眼于新的范式和应用程序,包括医学、机器人技术、商业、工业自动化、控制系统、交通、通讯、环境监测、生物医学系统、安全和电子服务、金融和经济。所有提交的方法和系统的共同特征是系统和环境的不断发展的性质。该期刊包含与以下相关的贡献:1)机器学习、人工智能、计算智能和数学建模的方法 2)来自自然和生物学的灵感,包括神经科学、生物信息学和分子生物学、量子物理学3) 在工程、商业、社会科学中的应用。
期刊主页投稿网址涉及主题 | 计算机科学人工智能数学机器学习工程类哲学物理生物统计程序设计语言社会学语言学算法社会科学心理学数据挖掘操作系统经济复杂系统量子力学数学优化计算机视觉认知心理学模式识别(心理学) |
出版信息 | 出版商: Springer Nature,出版周期: 6 issues per year,期刊类型: journal |
基本数据 | 创刊年份: 2010,原创研究文献占比: 93.24%,自引率:7.40%, Gold OA占比: 5.48% |
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