Speeding Up the Simulation Animals Diseases Spread: A Study Case on R and Python Performance in PDSA-RS Platform

Rodrigo Schneider, Felipe Machado, Celio Trois, Glênio Descovi, Vinícius Maran, Alencar Machado

2024

Abstract

The control and prevention of livestock diseases play a crucial role in safeguarding business continuity, simulating disease prevention and control measures are vital to mitigate future epidemics. In this sense, modelling systems can be an effective tool that allows the simulation of different ways of spreading diseases by configuring parameters allowing testing of different prevention measures. This work investigates enhancing a system that simulates disease spread processes in animals. The stochastic model system was developed in R; however, given a large amount of data and intense processing of stochastic functions that simulate spreading and control actions, it required optimization. We focused on translating and modifying it to Python using packages focused on data analysis, aiming to speed up the system execution time. We conducted experiments comparing high computational cost functions executed in the actual model R with the new proposal implemented in Python. The results showed that rewriting the code in Python has advantages such as performance in time execution, which in Python is more than four times faster than R, memory usage consumption in R uses 460 MB and 315 MB in Python.

Paper Citation

in Harvard Style

Schneider R., Machado F., Trois C., Descovi G., Maran V. and Machado A. (2024). Speeding Up the Simulation Animals Diseases Spread: A Study Case on R and Python Performance in PDSA-RS Platform. In Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-692-7, SciTePress, pages 651-658. DOI: 10.5220/0012556200003690

in Bibtex Style

@conference{iceis24,
author={Rodrigo Schneider and Felipe Machado and Celio Trois and Glênio Descovi and Vinícius Maran and Alencar Machado},
title={Speeding Up the Simulation Animals Diseases Spread: A Study Case on R and Python Performance in PDSA-RS Platform},
booktitle={Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2024},
pages={651-658},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012556200003690},
isbn={978-989-758-692-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 26th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - Speeding Up the Simulation Animals Diseases Spread: A Study Case on R and Python Performance in PDSA-RS Platform
SN - 978-989-758-692-7
AU - Schneider R.
AU - Machado F.
AU - Trois C.
AU - Descovi G.
AU - Maran V.
AU - Machado A.
PY - 2024
SP - 651
EP - 658
DO - 10.5220/0012556200003690
PB - SciTePress