Paper Info
Title
SBML for optimizing decision support's tools.
Abstract
Many theoretical works and tools on epidemiological field reflect the emphasis on decision-making Tools by both public health and the scientific community, which continues to increase. Indeed, in the epidemiological field, modeling tools are proving a very important way in helping to make decision. However, the variety, the large volume of data and the nature of epidemics lead us to seek solutions to alleviate the heavy burden imposed on both experts and developers. In this paper, we present a new approach: the passage of an epidemic model realized in Bio-PEPA to a narrative language using the basics of SBML language. Our goal is to allow on one hand, epidemiologists to verify and validate the model, and the other hand, developers to optimize the model in order to achieve a better model of decision making. We also present some preliminary results and some suggestions to improve the simulated model.
Year
DOI
Venue
2013
10.5121/csit.2013.3810
CoRR
Keywords
Field
DocType
finance
Epidemic model,Computer science,Decision support system,Narrative,Artificial intelligence,Management science,SBML,Machine learning
Journal
Volume
ISSN
Citations 
abs/1311.3837
Aircc.Proc. 3.8 (2013) 109-119
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Dalila Hamami121.72
Baghdad Atmani27018.72