Discrete-Time Stochastic Systems: Estimation and Control
Discrete-Time Stochastic Systems: Estimation and Control
Theory of Modeling and Simulation
Theory of Modeling and Simulation
Stochastic Discrete Event Systems: Modeling, Evaluation, Applications
Stochastic Discrete Event Systems: Modeling, Evaluation, Applications
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The paper starts from the human influenza's spreading phenomenon, as a complex of observable occurrences, and develops a stochastic process, defined as a set of procedures that convert its initial state into a sequence of different states during the phenomenon's lifespan. The Monte Carlo simulation method for a stochastic discrete event system is used. This system is completely described in terms of: entities, sequential states, transition tables of states, sets of input/output events, internal/external transition function, events/time advance function, input/output parameters. The simulation can encompass several contagion schema and health policy responses. Finally, some information about the software in the field is given.