Page 111 - 《软件学报》2021年第10期

王双成 等:基于贝叶斯网络的时间序列因果关系学习 3083

进一步的工作是提高因果关系和元因果关系的学习效率与可靠性,在因果关系结构数据集中考虑混合因
果关系变量,为因果关系变量引入时滞因素,并将因果关系用于低频宏观经济指标时间序列的定性与定量因果
分析,以及将元因果关系用于高频金融指标时间序列的因果关系演化分析和未来发展趋势判断等.

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