| 可能网络结构学习的依赖分析方法研究 |
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| 引用本文： | 冷翠平,王双成.可能网络结构学习的依赖分析方法研究[J].计算机工程与应用,2009,45(6):29-31. |
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| 作者姓名： | 冷翠平 王双成 |
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| 作者单位： | 上海立信会计学院 数学与信息学院，上海 201620 |
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| 基金项目： | 国家自然科学基金，上海高校选拔培养优秀青年教师科研专项基金，上海市市本级财政部门预算资助项目 |
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| 摘 要： | 贝叶斯网络是概率理论与图形模式的结合，被广泛用于不确定性问题求解，但不具有处理不准确性信息的能力。可能网络是可能理论、概率理论与图形模式的结合，可弥补贝叶斯网络这方面的不足。首先介绍关于可能网络的一些概念，并与贝叶斯网进行比较，然后给出一种基于依赖分析的可能网络结构学习方法。
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| 关 键 词： | 可能网络 贝叶斯网络 不确定性信息 不准确性信息 集值 |
| 收稿时间： | 2008-11-3 |
| 修稿时间： | 2008-12-1
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Study on dependency analysis method for learning possibilistic network structure |
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| LENG Cui-ping,WANG Shuang-cheng.Study on dependency analysis method for learning possibilistic network structure[J].Computer Engineering and Applications,2009,45(6):29-31. |
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| Authors: | LENG Cui-ping WANG Shuang-cheng |
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| Affiliation: | School of Mathematics and Information，Shanghai Lixin University of Commerce，Shanghai 201620，China |
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| Abstract: | Bayesian network is the connection of probability theory and graphical model and is widely used to solve the uncertainty problem.But it has deficiencies in dealing with the imprecise information.Possibilistic network is the combination of probability theory and possibilistic theory with graphical model which can remedy defect of Bayesian network.In this paper the concept of possibilistic networks is introduced.Then it is compared with Bayesian network and a method of the possibilistic network structure learning based on the dependency analysis is given. |
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| Keywords: | possibilistic network Bayesian network uncertain information imprecise information set-valued |
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