A System Dynamics Modeling Support System Based on Computational Intelligence

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@Article{abdelbari:2019:Systems,

• author = "Hassan Abdelbari and Kamran Shafi",
• title = "A System Dynamics Modeling Support System Based on Computational Intelligence",
• journal = "Systems",
• year = "2019",
• volume = "7",
• number = "4",
• keywords = "genetic algorithms, genetic programming",
• ISSN = "2079-8954",
• URL = "https://www.mdpi.com/2079-8954/7/4/47",
• DOI = "doi:10.3390/systems7040047",
• 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.",
• notes = "also known as \cite{systems7040047}",

}

Genetic Programming entries for Hassan Abdelbari Kamran Shafi

Citations