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  • 标题:SBML for Optimizing Decision Supports Tools
  • 本地全文:下载
  • 作者:Dalila Hamami ; Baghdad Atmani
  • 期刊名称:Computer Science & Information Technology
  • 电子版ISSN:2231-5403
  • 出版年度:2013
  • 卷号:3
  • 期号:8
  • 页码:109-119
  • DOI:10.5121/csit.2013.3810
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要: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 SB ML 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
  • 关键词:Epidemiology; simulation; modelling; Bio-PEPA; narrative language; SB ML
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