A survey of methods for data inclusion in system dynamics models: Methods, tools and applications
Name
Houghton, Siegel, Wirsch, Moulton, Madnick, Goldsmith (2014) A survey of methods for data inclusion in system dynamics models.pdf
Description
Author's final manuscript.
Size
4.12 MB
Format
Adobe PDF
Checksum (MD5)
16efde3851b58172fd9f9975e9b792f2
Author(s)
Houghton, James
Siegel, Michael
Wirsch, Anton
Moulton, Allen
Madnick, Stuart E.
Goldsmith, Daniel
Date Issued
July 20, 2014
Publisher
© The System Dynamics Society
Citation
Houghton, J., Siegel, M., Wirsch, A., Moulton, A., Madnick, S., & Goldsmith, D. (2014). A survey of methods for data inclusion in system dynamics models: Methods, tools and applications. In Pål Davidsen, & Etiënne A. J. A. Rouwette (Eds.), Proceedings of the 32nd International Conference of the System Dynamics Society. System Dynamics Society.
Version
Author's final manuscript.
Abstract
Numerical data is experiencing a renaissance because 1) traditional data such as census and economic surveys are more readily accessible 2) new sensors are measuring things that have never been measured before, and 3) previously 'unstructured' data - such as raw text, audio, images, and videos - is becoming more amenable to quantification. Because of this explosion and the popular buzz surrounding ‘Big Data’, clients expect to see strong incorporation of data methods into dynamic models, and it is imperative that System Dynamics Modelers are fully versed in the techniques for doing so. The SD literature contains surveys that explain methods for including data in system dynamics modeling, but techniques have continued to develop. This paper attempts to bring these surveys up to date, and serve as a menu of modern techniques.
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Attribution-NonCommercial-NoDerivs 3.0 United States
