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Forwards-backwards algorithm based on parallel factors

机译:基于并行因子的前向后退算法

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The study about highly efficient inference algorithms on dynamic Bayesian networks has become one of the focuses in the area of artificial intelligence. In order to improve the inference efficient of the improved forwards-backwards algorithm, we proposed the forwards-backwards algorithm based on parallel factors. After explaining the basic idea of the parallel factors, we defined the parallel factors, then introduced them to the forwards pass and backwards pass to realize the computation step sharing and reduce the amount of computation further. It is proved by the simulation experiments that the forwardsbackwards algorithm based on parallel factors is correct and efficient.
机译:关于动态贝叶斯网络上高效推理算法的研究已成为人工智能领域的重点之一。为了提高改进的前向后向算法的推理效率,提出了一种基于并行因子的前向后向算法。在解释了并行因子的基本思想之后,我们定义了并行因子,然后将它们引入前向和后向遍历,以实现计算步骤共享,并进一步减少了计算量。仿真实验证明,基于并行因子的正向算法是正确有效的。

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