Open Science Research Excellence
@article{(International Science Index):,
  title    = {Dynamic-Stochastic Influence Diagrams: Integrating Time-Slices IDs and Discrete Event Systems Modeling},
  author    = {Xin Zhao and  Yin-fan Zhu and  Wei-ping Wang and  Qun Li},
  country   = {},
  abstract  = {The Influence Diagrams (IDs) is a kind of Probabilistic Belief Networks for graphic modeling. The usage of IDs can improve the communication among field experts, modelers, and decision makers, by showing the issue frame discussed from a high-level point of view. This paper enhances the Time-Sliced Influence Diagrams (TSIDs, or called Dynamic IDs) based formalism from a Discrete Event Systems Modeling and Simulation (DES M&S) perspective, for Exploring Analysis (EA) modeling. The enhancements enable a modeler to specify times occurred of endogenous events dynamically with stochastic sampling as model running and to describe the inter- influences among them with variable nodes in a dynamic situation that the existing TSIDs fails to capture. The new class of model is named Dynamic-Stochastic Influence Diagrams (DSIDs). The paper includes a description of the modeling formalism and the hiberarchy simulators implementing its simulation algorithm, and shows a case study to illustrate its enhancements.
  {International Journal of Mathematical and Computational Sciences },  volume    = {4},
  number    = {7},
  year      = {2010},
  pages     = {952 - 959},
  ee        = {},
  url       = {},
  bibsource = {},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 43, 2010},