Druzovec M, Welzer T, Colnaric M, Gyorkos J
Faculty of Mechanical Engineering, University of Maribor, 2000 Maribor, Slovenia.
Int J Med Inform. 2001 Sep;63(1-2):51-60. doi: 10.1016/s1386-5056(01)00171-x.
First generation expert systems were using shallow knowledge based on heuristic information to solve a diagnostic problem. This approach has many disadvantages, which can be avoided by using deep knowledge. Diagnostic reasoning based on deep knowledge is called model-based diagnostics. Recently, the use of qualitative modeling in relation to deep knowledge in expert systems has become increasingly important. The main purpose of our contribution is to present the model-based diagnostic approach at a formal level. The originality of the presented formalization is the concept of the diagnostic space, the characterization of the minimal diagnoses, and the measurement. The formalization serves as the theoretical background to prove our view to the design of qualitative system models and to establish the diagnostic architecture called DISY. The qualitative system model in our diagnostic approach needs not to be specially adopted for use in the diagnostic domain. The only requirement is that it must simulate the system behavior expressed by normal or abnormal functioning of its components. Proposed DISY architecture is not complex and simply takes into an account the previous diagnostic result to obtain a new one from the additional observation-measurement (medical tests or examinations) of the system.
第一代专家系统使用基于启发式信息的浅层知识来解决诊断问题。这种方法有许多缺点，而使用深层知识可以避免这些缺点。基于深层知识的诊断推理称为基于模型的诊断。近年来，在专家系统中与深层知识相关的定性建模的应用变得越来越重要。我们贡献的主要目的是在形式层面上展示基于模型的诊断方法。所呈现的形式化的独特之处在于诊断空间的概念、最小诊断的特征描述以及度量。该形式化作为理论背景，用于证明我们对定性系统模型设计的观点，并建立称为DISY的诊断架构。我们诊断方法中的定性系统模型无需专门为诊断领域而采用。唯一的要求是它必须模拟由其组件的正常或异常功能所表达的系统行为。所提出的DISY架构并不复杂，只需考虑先前的诊断结果，以便从系统的额外观察测量（医学检查或检验）中获得新的诊断结果。
