Dynamic modification of online simulation system based on intelligence data-driven

To ensure the creditability of the online simulation system for decision-making, the method for dynamically modifying the online simulation based on intelligence data-driven is proposed. The intelligence data are divided into gradual data and fast data according to the change ratio. For describing the consistency between the simulation output and the intelligence data, the differences between the gradual data are depicted by the proximity of the position and the similarity of the shape, the fast data is decomposed into the trend item and stationary item, and the measure models of differences for each item are given. Furthermore, the modification set of the simulation model is gained via Latin hypercube sampling, the best modification scheme is selected by integrating the consistency indexes of the simulation output based on principal component analysis. Finally, the validity of the method is shown in the application.