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Mathematical and Computer Modelling of Dynamical Systems is a peer-reviewed journal published by Taylor & Francis, covering Numerical methods for differential equations, Model Reduction and Neural Networks, Advanced Control Systems Optimization.
| Publisher | Taylor & Francis |
|---|---|
| Reference style | Author–year (Chicago, T&F) Author–year — (Smith, 2023) in the text Smith, Ada, Ben Jones, and Cara Lee. 2023. "A Representative Article Title." Mathematical and Computer Modelling of Dynamical Systems 12 (3): 45–58.
Formats any DOI in Mathematical and Computer Modelling of Dynamical Systems style. No sign-up. |
| Publishes research in | Numerical methods for differential equations Model Reduction and Neural Networks Advanced Control Systems Optimization Modeling and Simulation Systems Control and Stability of Dynamical Systems |
| ISSN | 1387-3954 |
| Citation impact (2-yr) | 3.38 |
| h-index | 43 |
| i10-index | 305 |
| Total citations | 11,205 |
| Article processing charge | $1,533 |
| Open access | Yes |
| Top institutions publishing here | TU Wien |
| Journal website | www.tandfonline.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Bifurcation software is an essential tool in the study of dynamical systems. From the beginning (the first packages were written in the 1970's) it was also used in the modelling process, in particular to determine the values of critical parameters. More recently, it is used in a systematic way in the design of dynamical models…
Extended Kalman Filtering (EKF) is proposed for: (i) the extraction of a fuzzy model from numerical data; and (ii) the localization of an autonomous vehicle. In the first case, the EKF algorithm is compared to the Gauss–Newton nonlinear least-squares method and is shown to be faster. An analysis of the EKF convergence is given. In…
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This paper describes the identification of nonlinear dynamic systems with a Gaussian process (GP) prior model. This model is an example of the use of a probabilistic non-parametric modelling approach. GPs are flexible models capable of modelling complex nonlinear systems. Also, an attractive feature of this model is that the variance associated with the model…
Modelling and simulation of complex engineering systems are often relieved by a modular approach in which the global system is decomposed into subsystems. Advantages arise from independent and parallel modelling of subsystems over easy exchange of the resulting modules to the use of different software for each module. However, the modular simulation of the global…
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