Mathematical and Computer Modelling of Dynamical Systems: Methods, Tools and Applications in Engineering and Related Sciences
Mathematical and Computer Modelling of Dynamical Systems: Methods, Tools and Applications in Engineering and Related Sciences
Journal Title: Mathematical and Computer Modelling of Dynamical Systems: Methods, Tools and Applications in Engineering and Related Sciences
ISSN: 1387-3954
ISSN Online: 1744-5051
Publication Frequency: 6 issues per year
Impact Factor:
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Source Normalized Impact per Paper (SNIP):
SCImago Journal Rank (SJR):
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Aim & Scope:

The analysis and improvement of performance in complex systems, the adaptation of plants to new demands or conditions, and the design of ’optimal’ systems are a few of the challenges confronting engineers and systems scientists today. In many cases solutions to problems in areas such as these may be found through the use of appropriate mathematical models. The dynamic case, whether continuous time, discrete time of discrete-event, deterministic or stochastic, presents special challenges, and derivation of an appropriate solution depends strongly on the proper initial formulation of the goals and constraints. Increasingly this demands an interdisciplinary approach to modelling. Models can take the form of sets of equations, graphs or nets, or some combination of elements such as these. The derivation, combination, simplification and validation of models and sub-models are the main topics of Mathematical and Computer Modelling of Dynamical Systems , which provides an international forum for the presentation of new ideas in modelling and for the exchange of experience and knowledge through descriptions of specific applications. Original work will be published as regular papers or short notes dealing with a range of topics including the following:

Processes and methods for model formulation, identification, development, reduction and validation etc. (including guidelines and check lists) Automation of modelling and software aid for modelling The relationship between computational/simulation methods, the underlying mathematical formulation and real-world modelling problems Qualitative modelling including fuzzy and iterative approaches to modelling Modular modelling (especially applied to interdisciplinary fields such as mechatronic or controlled environmental systems) Learning networks in modelling Uncertainties in modelling The relationship between the modelling approach and problem solutions Comparisons of methods for modelling, model reduction and model validation effects of modelling errors on overall performance of engineering system (e.g. relationship between modelling and control design) Applications of modellingin the field of engineering systems Applications of modellingin other fields (such as environmental systems, biotechnology etc.) provided the methods or ideas presented are relevant in a number of areas or are of interest from a theoretical point of view Case studies allowing a comparison of ideas or methods

Consequently, computer simulation and description of mathematical methods and/or algorithms are restricted to the field of modelling and to the consequences of modelling. Only the most important facts about the latter should be discussed but not all the details of modelling languages or about mathematical methods and/or algorithms which is used to solve the task for which the (simulation) model was created. Modelling of the task including the modelling of the dynamic system, of restrictions, of goals etc. and the implications of the model used on solution and on solution methods are of primary interest.

Therefore, papers dealing with applications are accepted only when the purpose of the model, the assumptions (explicit and implicit) made in its development and the precise process of model validation are discussed carefully. Authors are requested to concentrate an those aspects which are of interest to a large community of engineers and scientists and to organize the paper so that it is stimulating and easily readable for engineers and scientists working in a wide range of application areas.

Further, a manuscript should be self-contained without being lengthy i.e. its contents should be able to be understood by readers that are not experts in that specific area of application and without consulting many articles in the literature.

2013 2-yearImpact Factor: 0.984 ©2014 Thomson Reuters, 2013 Journal Citation Reports®

Readership Engineers - especially electrical and control engineers, aerospace engineers, mechanical engineers, marine and offshore engineers, chemical engineers, safe engineers and civil engineers, mathematicians and computer scientists who are involved with applications of mathematical and computer modelling in the physical sciences, in biology, in medicine, in ecology and in other fields such as economics.
Peer Review Policy

All submitted manuscripts are subject to initial appraisal by the Editor. If found suitable for further consideration, papers are subject to peer review by independent, anonymous expert referees. All peer review is single blind and submissions can be made online at Review times For papers submitted in 2013, the time between original submission and receiving a first decision on a paper was on average 47 days, the median time was 34 days. Production times For papers accepted in 2013, the average time from acceptance to first online publication was 31 days, the median time was 29 days.

Subjects Covered & Scope: Currently known as Mathematical and Computer Modelling of Dynamical Systems: Methods, Tools and Applications in Engineering and Related Sciences (1998 - current) Formerly known as Mathematical Modelling of Systems (1995 - 1997)
Editor Board:


I. Troch - Institute for Analysis and Scientific Computing, Vienna University of Technology, Wiedner Hauptstrasse 8-10, 1040 Wien, Austria

Associate Editors:

J. McPhee - Systems Design Engineering, University of Waterloo, Ontario, Canada N2L 3G1
P.C. Müller - Group of Safety Control Engineering, University of Wuppertal, 42097 Wuppertal, Germany
D.J. Murray-Smith - Department of Electronics and Electrical Engineering, University of Glasgow, Glasgow G12 8LT, UK

Editorial Board:

P. C. Breedveld - University of Twente, The Netherlands
F. Breitenecker - Vienna University of Technology, Austria
F. E. Cellier - University of Arizona, USA
F. L. Chernousko - Russian Academy of Sciences, Russia
S. Engell - Universität Dortmund, Germany
G. Ferretti - Politecnico di Milano, Italy
B. A. Foss - Norwegian Institute of Technology, Norway
K. Furuta - Tokyo Denki University, Japan
R. Hanus - Free University of Brussels, Belgium
K. Juslin - VTT Technical Research Centre, Finland
R. Karba - University of Ljubljana, Slovenia
D. Karnopp - University of California, USA
N. A. Kheir - Oakland University, USA
L. Ljung - Linköping University, Sweden
J. V. R. Prasad - Georgia Institute of Technology, USA
J. Rudolph - Universität des Saarlandes, Germany
W. Schiehlen - Universität Stuttgart, Germany
K. Schlacher - Johannes Kepler University of Linz, Austria
S. Tzafestas - National Technical University of Athens, Greece
R. Viertl - Vienna University of Technology, Austria

Abtracting & Indexing:

Mathematical and Computer Modelling of Dynamical Systems is abstracted and indexed in Applied Mechanics Reviews; Astrophysics Data System;British Library Inside;EBSCO Databases;INSPEC®; ISI CompuMath Citation Index®; ISI Current Contents® - Engineering, Computing and Technology; ISI Science Citation Index Expanded?; Mathematical Reviews/MathSciNet; New Jour; SciBase; Scopus?; Zentralblatt MATH/Mathematics Abstracts and Zetoc.

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