Simulation, especially discrete event simulation (DES), is used in a variety of disciplines where numerical methods are difficult or impossible to apply. One problem with this method is that a sufficiently detailed simulation may take hours or days to execute, and multiple runs may be needed in order to generate the desired results. Paral-lel discrete event simulation (PDES) has been explored for many years as a method to decrease the time taken to ex-ecute a simulation. Many protocols have been developed which work well for particular types of simulations, but perform poorly when used for other types of simulations. Often it is difficult to know a priori whether a particular protocol is appropriate for a given problem. In this work, an adaptive synchronization method (ASM) is developed which works well on an entire spectrum of problems. The ASM determines, using an artificial neural network (ANN), the likelihood that a particular event is safe to process. physical process is then simulated by a logical process (LP).