| Full text | |
| Author(s): |
Nakamura, Gilberto M.
;
Souza, Alinne C. C.
;
Souza, Francisco C. M.
;
Bulcao-Neto, Renato F.
;
Martinez, Alexandre S.
;
Macedo, Alessandra A.
Total Authors: 6
|
| Document type: | Journal article |
| Source: | IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS; v. 19, n. 2, p. 10-pg., 2022-03-01. |
| Abstract | |
Symmetries express the invariance of a system towards sets of mathematical transformations. In more practical terms, symmetries greatly reduce or simplify the computational efforts required to evaluate relevant properties of a system. In this paper, two methods are proposed to implement spin symmetries which simplify the analysis of the spreading of diseases in an agent-based epidemic model. We perform a set of simulations to measure the efficiency gains compared to traditional methods. Our findings show symmetry-based algorithms improve the performance of the Monte Carlo simulation and the exact Markov process. (AU) | |
| FAPESP's process: | 16/13206-4 - Semnatic Enrichment of Medical Information from Networking Complex Heterogeneous |
| Grantee: | Alessandra Alaniz Macedo |
| Support Opportunities: | Regular Research Grants |