When Machine Learning Meets Complex Systems
Submission Deadline: July 21, 2019View Collection
This Focus Issue will concentrate on the new algorithms, strategies and techniques with machine learning applied to complex systems, and on applying complex systems techniques to leverage the performance of machine learning techniques with high-efficiency. This Focus Issue provides a platform to facilitate interdisciplinary research and to share the most recent developments in various related fields.
Topics covered include, but are not limited to:
- Recurrence plots by complex networks
- Spatiotemporal chaos
- Community detection in complex networks
- Data analytics of complex systems and their dynamics
- Brain analysis by machine learning
- Vital nodes/link identification in complex networks
- Control and optimization in complex power grids
- Identification/Control of complex systems by machine learning
- Physical realizations of reservoir computers
- Security and resilience analysis in complex systems by machine learning
- Computer vision, formation control and navigation in multi-agent systems
- Exponential random graph models
- Bayesian modeling for complex systems
- Inferring causal interactions
- Forecasting future system evolution
- Applications in climate, social science, economics, engineering, biology, etc.
Guest Editors
Yang Tang – East China University of Science and Technology
Jurgen Kurths – Humboldt-Universitat zu Berlin, Potsdam Institute for Climate Impact Research
Wei Lin – Fudan University
Liupco Kocarev – Macedonian Academy of Sciences and Arts
Edward Ott – University of Maryland, College Park
Submission Deadline: July 21, 2019View Collection