The aim of this study was to develop and explore a stochastic lattice gas cellular automata （LGCA） model for epidemics. A computer program was development in order to implement the model. An irregular grid of cells ...The aim of this study was to develop and explore a stochastic lattice gas cellular automata （LGCA） model for epidemics. A computer program was development in order to implement the model. An irregular grid of cells was used. A susceptible-infected-recovered （SIR） scheme was represented. Stochasticity was generated by Monte Carlo method. Dynamics of model was explored by numerical simulations. Model achieves to represent the typical SIR prevalence curve. Performed simulations also show how infection, mobility and distribution of infected individuals may influence the dynamics of propagation. This simple theoretical model might be a basis for developing more realistic designs.展开更多
This paper is standing on the recent viewpoint originated from relevant industrial practices that well or-ganized tracing, representing and feedback(TRF) mechanism of material-flow information is crucial for system ut...This paper is standing on the recent viewpoint originated from relevant industrial practices that well or-ganized tracing, representing and feedback(TRF) mechanism of material-flow information is crucial for system utility and usability of manufacturing execution systems(MES), essentially, for activities on the side of multi-level decision making and optimization mainly in the planning and scheduling. In this paper, we investigate a key issue emphasized on a route of multi-level information evolution on the side of large-scale feedback, where material-flow states could evolve from the measuring data(local states) to networked event-type information cells(global states) and consequently to the key performance indicators(KPI) type information(gross states). Importantly, with adapta-bilities to frequent structural dynamics residing in running material flows, this evolving route should be modeled as a suit of sophisticated mechanism for large-scale dynamic states tracking and representing so as to upgrade accu-racy and usability of the feedback information in MES. To clarify inherent complexities of this evolving route, the investigated issue is demonstrated from extended process systems engineering(PSE) point of view, and the TRF principles of the multi-level feedback information(states) are highlighted under the multi-scale methodology. As the main contribution, a novel mechanism called TRF modeling mechanism is introduced.展开更多
文摘The aim of this study was to develop and explore a stochastic lattice gas cellular automata （LGCA） model for epidemics. A computer program was development in order to implement the model. An irregular grid of cells was used. A susceptible-infected-recovered （SIR） scheme was represented. Stochasticity was generated by Monte Carlo method. Dynamics of model was explored by numerical simulations. Model achieves to represent the typical SIR prevalence curve. Performed simulations also show how infection, mobility and distribution of infected individuals may influence the dynamics of propagation. This simple theoretical model might be a basis for developing more realistic designs.
基金Supported by the National Basic Research Program of China(2012CB720500)the National High Technology Research and Development Program of China(2012AA041102)
文摘This paper is standing on the recent viewpoint originated from relevant industrial practices that well or-ganized tracing, representing and feedback(TRF) mechanism of material-flow information is crucial for system utility and usability of manufacturing execution systems(MES), essentially, for activities on the side of multi-level decision making and optimization mainly in the planning and scheduling. In this paper, we investigate a key issue emphasized on a route of multi-level information evolution on the side of large-scale feedback, where material-flow states could evolve from the measuring data(local states) to networked event-type information cells(global states) and consequently to the key performance indicators(KPI) type information(gross states). Importantly, with adapta-bilities to frequent structural dynamics residing in running material flows, this evolving route should be modeled as a suit of sophisticated mechanism for large-scale dynamic states tracking and representing so as to upgrade accu-racy and usability of the feedback information in MES. To clarify inherent complexities of this evolving route, the investigated issue is demonstrated from extended process systems engineering(PSE) point of view, and the TRF principles of the multi-level feedback information(states) are highlighted under the multi-scale methodology. As the main contribution, a novel mechanism called TRF modeling mechanism is introduced.
