Generalized Causal Qualitative Networks and Its Fusion Model for Qualitative Modeling of Bayesian Networks

Hong-bin Fang
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Abstract

Constructing the structure of BN through qualitative approachability is feasible according to fusion. In this paper, a new concept, generalized causal qualitative networks, is put forward as well as its fusion model is given for qualitative modeling of corresponding Bayesian networks through qualitative approachability.
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广义因果定性网络及其融合贝叶斯网络定性建模模型
根据融合理论,通过定性逼近来构建BN的结构是可行的。本文提出了广义因果定性网络的概念,并通过定性逼近给出了广义因果定性网络的融合模型,对相应的贝叶斯网络进行定性建模。
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