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Dynamic Bayesian networks (DBNs) can effectively perform modeling and qualitative reasoning for many dynamic systems. However, most of its inference algorithms involve complicated graphical transformations that are hard to program and time-consuming to compute. This article proposes a new recursive inference algorithm, which is a purely numerical method derived from probability theory and the characteristics...