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2016-09-29 发布于北京
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The application of Bayesian network in Uncertainty management.doc

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The application of Bayesian network in Uncertainty management.doc

The application of Bayesian network in Uncertainty management 　　Abstract：Uncertainty management is playing an important role in many fields,especially in AI (artificial intelligence). This paper introduces the concept of probability and the Bayesian Network which are widely used in uncertainty management field.Additionally, two examples are completed and analyzed in the paper. 　　Keywords：Uncertainty management;Probability;Bayesian network 　　1 INTRODUCTION(WHAT IS UNCERTAINTY?) 　　People always deal with all sorts of information everyday.However,most of the information for human is imperfect.This information is fuzzy,inconsistent or uncertain.When designing a system,what people can do is to make it as an ideal one. 　　However,the real world is often not ideal.When people want to cover whole situations,they may use imprecise data to describe the real situation. That means there is uncertainty in the system.It is not good idea to just ignore all the uncertain information.The better way to deal with it is to know how to do uncertainty management. 　　2 TYPE OF UNCERTAINTY 　　Uncertainty issues are partitioned into those that deal with fuzziness and those that deal with ambiguity.There are many types of uncertainty.And in Artificial Intelligence,uncertainty management is an important work to do.Basically,several types of uncertainty situation are as follows: 　　A.Inconsistency.This often arises when confliction occurs.This means there are two conditions,however, satisfying one of them means not satisfying another one. 　　B.Multiple options.People many have many tourism sites for them to choose.And it not clear which sites they may choose.The economic factor might decide which of them may be chosen. 　　C.Nondeterminism.When software is designed, people do not know whether the output will meet the requirement before testing it.In other words,it is not determined. 　　D.No knowledge as negation.In knowledge based system,if the one rule is not inside the system,then the