Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

The Role of Big Data Analytics in Developing System Dynamic Models

Version 1 : Received: 31 October 2018 / Approved: 5 November 2018 / Online: 5 November 2018 (02:34:30 CET)

How to cite: Kianmehr, H.; Sabounchi, N.; Begdache, L. The Role of Big Data Analytics in Developing System Dynamic Models. Preprints 2018, 2018110074. https://doi.org/10.20944/preprints201811.0074.v1 Kianmehr, H.; Sabounchi, N.; Begdache, L. The Role of Big Data Analytics in Developing System Dynamic Models. Preprints 2018, 2018110074. https://doi.org/10.20944/preprints201811.0074.v1

Abstract

Dietary factors are one of the risk factors that can impact the brain chemistry, which leads to mental distress. Based on our data mining approach, we found that mental distress in men is associated with eating unhealthy food. Our aim in this paper is to apply results from our big data analytics approach to inform system dynamics (SD) modeling to investigate the causal relationships between brain structures, nutrients from food and dietary supplements, and mental health. We perform descriptive analysis based on a large data set to estimate the SD modeling parameters. Finally, we calibrate the model towards a time series data collected for individuals on their dietary and distress patterns. The results reveal that bridging these different methodologies leads to further insights from the SD model and decreases the error of calibrated parameter values. Future research is needed to validate our initial results for investigating the relationship between mental distress and dietary intake.

Keywords

system dynamics modeling; big data; mental distress; diet

Subject

Medicine and Pharmacology, Psychiatry and Mental Health

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