Abstract: A first learning unit (101) learns a difference model (111) for predicting a difference between current monitoring data that is monitoring data obtained by monitoring a monitoring target at each time point and at each of a plurality of monitoring points and is monitoring data at a current time point, and past monitoring data that is monitoring data at each of a plurality of past time points; a second learning unit (102) learns a prediction model (past) (112) for predicting variation of the monitoring target using the past monitoring data; a first generation unit (103) generates corrected past data using the difference model (111), by correcting a difference between the past monitoring data and the current monitoring data; and a third learning unit (104) learns a prediction model (current) (113) for predicting variation of the monitoring target using the current monitoring data, the difference model (111), the prediction model (past) (112), and the corrected past data, whereby variation of the monitoring targe

Abstract: A vector field setting unit (102) sets a vector field for providing virtual force for reproducing, in a region in which a moving body moves, movement of the moving body in a certain direction, and a simulation unit (104) simulates the movement of the moving body in the region, based on a movement model to which a parameter for simulating the movement of the moving body is set and the vector field set by the vector field setting unit, whereby the movement of the moving body is appropriately simulated even when the movement of the moving body is unusual.