Name
Abstract | ||
|---|---|---|
High-level Petri nets (HLPNs) are an expressive formalism well supported by a number of tools that automate the editing and the interactive simulation of models and some kinds of analytical techniques, mainly based on state-space exploration. Structural analysis of HLPNs is, however, a challenging task not yet adequately supported and it is often accomplished via the unfolding of an HLPN into a corresponding low-level Petri Net. An approach to derive a system of Ordinary Differential Equations (ODEs) from a Stochastic Symmetric Net (SSN) has been proposed a few years ago, based on the net's unfolding and subsequent grouping of similar equations. This method has been recently improved by providing an algorithm that directly derives a compact ODE system (from a partially unfolded net) in a symbolic way, through algebraic manipulation of SSN annotations. In this paper, we present the automation of the calculus of Symbolic ODEs (SODEs) for SSN models as a new module of SNexpression, a tool for the symbolic structural analysis of Symmetric Nets. An application of the tool/technique to a variant of a SIRS epidemic model including antibiotic resistance is also described. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/MASCOTS.2019.00015 | 2019 IEEE 27th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS) |
Keywords | Field | DocType |
High-Level Petri Nets, Symmetric Nets, Symbolic structural relations, Ordinary Differential Equations | Algebra,Computer science,Ode,Distributed computing | Conference |
ISSN | ISBN | Citations |
2375-0227 | 978-1-7281-4950-9 | 0 |
PageRank | References | Authors |
0.34 | 10 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marco Beccuti | 1 | 195 | 26.04 |
| Lorenzo Capra | 2 | 88 | 18.08 |
| Massimiliano De Pierro | 3 | 119 | 9.28 |
| G. Franceschinis | 4 | 1075 | 70.58 |
| Laura Follia | 5 | 2 | 1.83 |
| Simone Pernice | 6 | 1 | 1.40 |