举例来说,<font color="#ff8000">贝叶斯网络 Bayesian network </font>表示多个概率事件的关联网络。顶点表示事件,后续事件的发生可能性则可以通过其在有向无环图的前驱节点的发生概率计算出来。<ref>{{citation|title=Probabilistic Boolean Networks: The Modeling and Control of Gene Regulatory Networks|publisher=Society for Industrial and Applied Mathematics|first1=Ilya|last1=Shmulevich|first2=Edward R.|last2=Dougherty|year=2010|isbn=978-0-89871-692-4|page=58|url=http://books.google.com/books?id=RfshqEgO7KgC&pg=PA58}}.</ref>在此基础上,一个有向无环图的<font color="#ff8000"> 端正图 Moral graph </font>通过以下方法而得到:将单个顶点的所有父节点之间添加一条无向边,再将所有的有向边换成无向边。<ref>{{citation |last1= Cowell |first1= Robert G. |author2-link=Philip Dawid|last2=Dawid|first2=A. Philip|author3-link=Steffen Lauritzen|last3=Lauritzen|first3=Steffen L.|author4-link=David Spiegelhalter|last4=Spiegelhalter|first4=David J.|title= Probabilistic Networks and Expert Systems |publisher= Springer |year= 1999 |isbn= 0-387-98767-3 |chapter= 3.2.1 Moralization|pages= 31–33 }}.</ref> | 举例来说,<font color="#ff8000">贝叶斯网络 Bayesian network </font>表示多个概率事件的关联网络。顶点表示事件,后续事件的发生可能性则可以通过其在有向无环图的前驱节点的发生概率计算出来。<ref>{{citation|title=Probabilistic Boolean Networks: The Modeling and Control of Gene Regulatory Networks|publisher=Society for Industrial and Applied Mathematics|first1=Ilya|last1=Shmulevich|first2=Edward R.|last2=Dougherty|year=2010|isbn=978-0-89871-692-4|page=58|url=http://books.google.com/books?id=RfshqEgO7KgC&pg=PA58}}.</ref>在此基础上,一个有向无环图的<font color="#ff8000"> 端正图 Moral graph </font>通过以下方法而得到:将单个顶点的所有父节点之间添加一条无向边,再将所有的有向边换成无向边。<ref>{{citation |last1= Cowell |first1= Robert G. |author2-link=Philip Dawid|last2=Dawid|first2=A. Philip|author3-link=Steffen Lauritzen|last3=Lauritzen|first3=Steffen L.|author4-link=David Spiegelhalter|last4=Spiegelhalter|first4=David J.|title= Probabilistic Networks and Expert Systems |publisher= Springer |year= 1999 |isbn= 0-387-98767-3 |chapter= 3.2.1 Moralization|pages= 31–33 }}.</ref> |