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Compiling knowledge of different kinds for diagnosis of traffic congestion

机译:编制不同种类的知识,以诊断交通拥堵

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Car traffic is one of the widespread applications where domain experts need to employ different kinds of knowledge for diagnosing a single fault. The application provides application-oriented kinds like fault trees, heuristics, fault models, and functional models. Hence, for knowledge based diagnosis, a problem solving method is needed which is able to evaluate multiple kinds of knowledge. The presented approach uses knowledge compilation to transpose knowledge of different kinds to one target kind. The required method is developed as a method using the target kind. The problem of specifying a target kind which overlaps with application-oriented kinds, however, is approached by starting from the task of diagnosis which defines a task- oriented kind covering knowledge necessary for solving the task. Since necessary knowledge must be available in application-oriented kinds, the task- oriented kind overlaps with each of them, and its problem solving method serves as the required method.
机译:汽车交通是域专家需要采用不同类型的知识来诊断单个故障的广泛应用程序之一。该应用程序提供了面向应用的种类,如故障树,启发式,故障模型和功能模型。因此,对于基于知识的诊断,需要解决问题的解决方法,其能够评估多种知识。呈现的方法使用知识汇编将不同种类的知识转换为一个目标类型。使用目标类的方法开发所需的方法。然而,通过从诊断的任务开始,接近以应用面向应用的种类重叠的目标类型的问题是通过定义解决任务所需的任务导向的涵盖知识。由于必要的知识必须以涂抹为导向的种类,因此与它们中的每一个具有任务导向的类重叠,并且其问题解决方法用作所需的方法。

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