同步(交流)
计算机科学
博弈论
进化博弈论
非线性系统
动力系统理论
预警系统
光学(聚焦)
复杂系统
数据科学
时间序列
复杂网络
人工智能
机器学习
数学
计算机网络
频道(广播)
物理
量子力学
电信
数理经济学
万维网
光学
作者
Dibakar Ghosh,Norbert Marwan,Michael Small,Changsong Zhou,Jobst Heitzig,Aneta Koseska,Peng Ji,István Z. Kiss
出处
期刊:Chaos
[American Institute of Physics]
日期:2024-10-01
卷期号:34 (10)
被引量:1
摘要
This Focus Issue covers recent developments in the broad areas of nonlinear dynamics, synchronization, and emergent behavior in dynamical networks. It targets current progress on issues such as time series analysis and data-driven modeling from real data such as climate, brain, and social dynamics. Predicting and detecting early warning signals of extreme climate conditions, epileptic seizures, or other catastrophic conditions are the primary tasks from real or experimental data. Exploring machine-based learning from real data for the purpose of modeling and prediction is an emerging area. Application of the evolutionary game theory in biological systems (eco-evolutionary game theory) is a developing direction for future research for the purpose of understanding the interactions between species. Recent progress of research on bifurcations, time series analysis, control, and time-delay systems is also discussed.
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