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Probabilistic Inference and Elicitation of Structured Expert Knowledge in Industrial Megaprojects

机译:工业大型项目中结构化专家知识的概率推断和启发

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The uniqueness of megaprojects requires any effort to make sense of their behavior to successfully utilize expert knowledge. Success of industrial megaprojects relies heavily on the knowledge and experience of the owners, project managers, engineers, financiers and other organizations and parties within the project. This valuable project knowledge is held within organizations either as explicit and in documents, or, tacit and by the members of the project team. Quantifying and elicitation of this knowledge requires a framework that outlines its utilization. This paper outlines a methodology to systematically collect expert knowledge for probabilistic reasoning on megaproject behavior. The reasoning process is developed based on the failure path and driver view of project risk and failures mechanism. Results of a pilot survey study on the method, along with the created probabilistic model is presented.
机译:大型项目的独特性需要做出任何努力来理解其行为,以成功利用专家知识。工业大型项目的成功很大程度上取决于业主,项目经理,工程师,金融家以及项目中其他组织和团体的知识和经验。这些宝贵的项目知识以明示和文档形式保存在组织中,或者默认地由项目团队的成员保存。量化和启发这种知识需要一个概述其利用的框架。本文概述了一种方法,可以系统地收集有关大型项目行为概率推理的专家知识。基于故障路径和项目风险与故障机制的驱动程序视图来开发推理过程。介绍了对该方法进行的初步调查研究的结果,以及创建的概率模型。

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