Sensitivity analysis of a predictive model of social network impact on obesity and its chronic complications
SeMA Journal, ISSN: 2281-7875, Vol: 81, Issue: 2, Page: 193-218
2024
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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Article Description
In this paper, we propose a mathematical model based on employing social networks in supporting the general health of obese people through positive behaviors related to nutrition and physical activity within these networks. The proposed model is represented mathematically by a non-linear time system of ordinary differential equations. We analyze the stability of the equilibria with the negative and positive effects of social networks. Then, we perform sensitivity analyses on our model to determine the relative importance of model parameters to reduce complications due to obesity. Finally, numerical simulation results are obtained and displayed in graphical profiles. The results of our model and the health ramifications are then raised, discussed, and confirmed by other researchers’ results. This study is a theoretical study and is thought to be useful for other work to do.
Bibliographic Details
Springer Science and Business Media LLC
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