Machine Learning for Dynamical Systems
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Dynamical Systems".
Deadline for manuscript submissions: 31 July 2024 | Viewed by 1007
Special Issue Editors
Interests: dynamical systems; delay; neural network
Special Issue Information
Dear Colleagues,
Dynamical systems theory is mainly concerned with describing the long-term qualitative behavior of dynamical systems, or piecewise smooth dynamical systems, which can typically be described as various differential equations such as ordinary differential equations, functional differential equations, stochastic differential equations, difference differential equations, partial differential equations, and so on. However, the qualitative behavior of dynamical systems is understood from models, which are often approximations of the observed reality. It requires a detailed understanding of the processes to be analyzed. On the other hand, the field of machine learning is concerned with algorithms designed to accomplish a certain task, whose performance improves with the input of more data. The machine learning approach is becoming increasingly important in many applications. The aim of this Special Issue is to focus on recent developments in machine learning and analyze dynamic systems on the basis of observed data rather than the models themselves.
Dr. Chunhua Feng
Prof. Dr. Fred Roush
Guest Editors
Manuscript Submission Information
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Keywords
- dynamical system
- data
- machine learning
