Aims & Scope
Journal of Data and Dynamic Systems aims at publishing high-quality research papers and review papers broadly related to nonlinear dynamics of data, models, systems and their applications.The principal areas of interest of this journal are the following:
- Dynamics of neural networks and complex systems;
- Modelling, simulation and optimization of physics-oriented systems;
- Data modelling and learning dynamical systems;
- The quantitative analysis of dynamic systems and machine learning;
- Statistical modelling and learning of dynamic processes
- Control and Machine Learning
Papers that analyze dynamical systems based on observational data or utilize tools of dynamical systems theory to analyze data algorithms are particularly welcome.