Journal Menu► ▼ Journal Menu
Journal Browser► ▼ Journal Browser
Special Issue "Optimized Machine Learning Algorithms for Modeling Dynamical Systems"
A special issue of Symmetry (ISSN 2073-8994).
Deadline for manuscript submissions: 31 March 2020.
2: ICRIOS - The Invernizzi Centre for Research in Innovation, Organization, Strategy and Entrepreneurship,Bocconi University - Department of Management and Technology, Via Sarfatti, 25, 20136 Milano (MI) Italy, Office Room: Grafton Building - 4th Floor - Room A2-04
Tel. (+39) 0965 1695446/Tel.: (+39) 02 5836 6130
Interests: mathematical economics; game theory; optimization
2: Center for Dynamics, Department of Mathematics, Technische Universität Dresden, Germany
Let us ponder those machine learning algorithms that predict real dynamical systems.
Mathematical objects used to make models of physical phenomena dependent on time are dynamical systems. These models are used in economic forecasting, medical issues, environmental modelings, etc. There is an overlap between machine learning and dynamical systems. To address this relation, let us assume a framework for dynamical system learning, using the idea of instrumental–variable regression to transform dynamical system learning to a sequence of machine learning problems. This transformation allows applying a strong literature on machine learning to incorporate many types of prior knowledge. Hence, a family of fast and practical learning algorithms for a variety of dynamical system models are employed to forecast the real behavior of such dynamical systems precisely. Further, machine learning folks often use dynamical systems’ taxonomy and reformulate it to some fancy term to make the idea sound sort of new.
The aim of this Special Issue is to attract leading researchers in these areas in order to include new high-quality results on these topics involving their dynamical properties as well as their symmetry characteristics, both from a theoretical and an applied point of view. Please note that all submitted papers must be within the general scope of the Symmetry journal.
Prof. Dr. Massimiliano Ferrara
Dr. Mehdi Salimi
Dr. Ali Ahmadian
Dr. Bruno Antonio Pansera
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- machine learning
- supervised algorithms
- unsupervised algorithms
- dynamical systems
- real-world applications