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Projet EMS RP est un projet open-source dont l’objectif est d’être utilisé comme aide médicale pour tous les types de rôle-play contenant des interventions d’urgence.
In this simulation, the intensity of the intervention is periodically varied over a period of time. Consider a case in which the government intervention issues a restraint or ban on going out and contact of people changes.
Predicting outcomes of educational interventions before investing in large-scale implementation efforts in school settings is essential for educational policy-making. However, due to time and resource limitations, conducting longitudinal, large-scale experiments testing outcomes of interventions in authentic settings is difficult. Here, we introduce the deep learning method as a way to address this issue and illustrate the use of the deep learning method for the prediction of intervention outcomes through a MATLAB implementation. The presented deep learning method extracts predictable patterns from an empirical dataset to simulate large-scale intervention outcomes. Findings from our simulations suggest that the deep learning applied simulation model can predict intervention outcomes significantly more accurately compared to the traditional regression analysis methods.
A brief analysis on the performance of the aviation industry through indicators of cancellation rate, on-time rate, and average delay minutes, fitted by and to forecast with reasonable ARIMA models.
Feature based examples
Comprehensive examples