Mathematical and Computer Modelling of Dynamical Systems

Aims & Scope

Mathematical and Computer Modelling of Dynamical Systems (MCMDS) publishes high quality international research that presents new ideas and approaches in the derivation, simplification, and validation of models and sub-models of relevance to complex (real-world) dynamical systems.

The journal brings together engineers and scientists working in different areas of application and/or theory where researchers can learn about recent developments across engineering, environmental systems, and biotechnology amongst other fields.

As MCMDS covers a wide range of application areas, papers aim to be accessible to readers who are not necessarily experts in the specific area of application.

MCMDS welcomes original articles on a range of topics including: -methods of modelling and simulation- automation of modelling- qualitative and modular modelling- data-based and learning-based modelling- uncertainties and the effects of modelling errors on system performance- application of modelling to complex real-world systems.

Metrics & Ranking

Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Directory of Open Access Journals (DOAJ)
• Web of Science

Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Computer Science, Engineering and Mathematics, designed to support cutting-edge academic discovery.

Licensing & Copyright

This journal operates under an Open Access model. Articles are freely accessible to the public immediately upon publication. The content is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), allowing users to share and adapt the work with proper attribution.

Copyright remains with the author(s), and no permission is required for non-commercial use, provided the original source is cited.

Policy Links

This section provides access to essential policy documents, guidelines, and resources related to the journal’s publication and submission processes.

• Aims scope
• Homepage
• Oa statement
• Author instructions
• License terms
• Review url
• Board url
• Copyright url
• Plagiarism url
• Preservation url
• Apc url
• License

Plagiarism Policy

This journal follows a plagiarism policy. All submitted manuscripts are screened using reliable plagiarism detection software to ensure originality and academic integrity. Authors are responsible for proper citation and acknowledgment of all sources, and any form of plagiarism, including self-plagiarism, will not be tolerated.

For more details, please refer to our official: Plagiarism Policy.

APC Details

The journal’s Article Processing Charge (APC) policies support open access publishing in Computer Science, Engineering and Mathematics, ensuring accessibility and quality in research dissemination.

This journal requires an Article Processing Charge (APC) to support open access publishing, covering peer review, editing, and distribution. The current APC is 2,195.00 USD. Learn more.

Explore journals without APCs for alternative publishing options.

Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• New features of the software M<scp>at</scp>C<scp>ont</scp>for bifurcation analysis of dynamical systems

  Citation: 491

  Authors: A., W., Yu. A., H. G.E., B.

• Extended Kalman filtering for fuzzy modelling and multi-sensor fusion

  Citation: 266

  Authors: G., S.

• Model Based Design of a Novel Process for Nitrogen Removal from Concentrated Flows

  Citation: 184

  Authors: C., M.C.M., J.J.

• Dynamic systems identification with Gaussian processes

  Citation: 159

  Authors: Juš, Agathe, Blaž, Roderick

• Two Methods of Simulator Coupling

  Citation: 136

  Authors: R., W.

• A training set and multiple bases generation approach for parameterized model reduction based on adaptive grids in parameter space

  Citation: 118

  Authors: Bernard, Markus, Mario

• Crop prediction based on soil and environmental characteristics using feature selection techniques

  Citation: 117

  Authors: A., G., S.P.

• Balanced truncation model reduction of second-order systems

  Citation: 113

  Authors: Timo, Tatjana

• Modelling of thermo-hydraulic power generation processes using Modelica

  Citation: 98

  Authors: Francesco, Alberto

• Application of POD and DEIM on dimension reduction of non-linear miscible viscous fingering in porous media

  Citation: 90

  Authors: Saifon, Danny C.