A System Dynamics Modeling Support System Based on Computational Intelligence
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- @Article{abdelbari:2019:Systems,
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author = "Hassan Abdelbari and Kamran Shafi",
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title = "A System Dynamics Modeling Support System Based on
Computational Intelligence",
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journal = "Systems",
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year = "2019",
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volume = "7",
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number = "4",
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keywords = "genetic algorithms, genetic programming",
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ISSN = "2079-8954",
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URL = "https://www.mdpi.com/2079-8954/7/4/47",
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DOI = "doi:10.3390/systems7040047",
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abstract = "System dynamics (SD) is a complex systems modelling
and simulation approach with wide ranging applications
in various science and engineering disciplines. While
subject matter experts lead most of the model building,
recent advances have attempted to bring system dynamics
closer to fast growing fields such as data sciences.
This may prove promising for the development of novel
support methods that augment human cognition and
improve efficiencies in the model building process. A
few different directions have been explored recently to
support individual modelling stages, such as the
generation of model structure, model calibration and
policy optimisation. However, an integrated approach
that supports across the board modelling process is
still missing. In this paper, a prototype integrated
modelling support system is presented for the purpose
of supporting the modellers at each stage of the
process. The proposed support system facilitates
data-driven inferring of causal loop diagrams (CLDs),
stock-flow diagrams (SFDs), model equations and the
estimation of model parameters using computational
intelligence (CI) techniques. The ultimate goal of the
proposed system is to support the construction of
complex models, where the human power is not enough.
With this goal in mind, we demonstrate the working and
utility of the proposed support system. We have used
two well-known synthetic reality case studies with
small models from the system dynamics literature, in
order to verify the support system performance. The
experimental results showed the effectiveness of the
proposed support system to infer close model structures
to target models directly from system time-series
observations. Future work will focus on improving the
support system so that it can generate complex models
on a large scale.",
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notes = "also known as \cite{systems7040047}",
- }
Genetic Programming entries for
Hassan Abdelbari
Kamran Shafi
Citations