Predictive analytics using statistical, learning, and ensemble methods to support real-time exploration of discrete event simulations
Our approach enables fast, accurate forecasts of discrete event simulations. The framework copes with high dimensionality and voluminous datasets. We facilitate simulation execution with cycle scavenging and cloud resources. We create and evaluate several predictive models, including ensemble methods. Our framework is made accessible to end users through an interactive web interface.
discrete event simulation latin hypercube sampling distributed execution cloud infrastructure