近幾年中，貝氏網路方法是常用於各種領域的有效分析方法，然而在營建工程方面，面對著許多的不確定性安全風險，甚至缺乏歷史資料，造成某部分的領域無法正確獲取機率加以分析。在缺乏可用的資料之下，如何利用有效率以及準確率高的方法來獲取各因子狀態的發生機率便成了重要的課題。
本論文架構完整的專家主觀意識機率方法流程，針對在缺乏歷史資料下，探討如何透過專家主觀意識的方法引導出貝氏網路中各條件機率的數值，並試圖在流程中納入提高獲取效率、節省耗費時間的軟體工具加以使用，據此以讓貝氏網路後續能夠藉由可靠性高的機率數值加以分析。

Bayesian Network is an effective analysis method, and it is used in many domains in recent year. In construction engineering, many risk factors bring much uncertainty, and analyst cannot obtain the correct probabilities because of the lack of historical data. In the situation, how to obtain the probabilities of all the factors in every state will become an important topic.
In order to build a method process to acquire experts’ subjective probabilities, this research will investigate how to obtain the accurate values in the conditional probability table (CPT) of Bayesian Network by experts’ subjective judgment elicitation if there is lack of the historical data. At the same time, the research will also bring an useful software into the method process that analyst could obtain the values efficiently, and thus use the accurate and reliable values to proceed the Bayesian Network Analysis in order to create the valid results.

中文部分

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英文部分

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Norman E. Fenton, Martin Neil, and Jose Galan Caballero (2007). Using Ranked Nodes to Model Qualitative Judgments in Bayesian Networks, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 19, NO. 10, pp. 1420-1432.

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