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Designing rule-based expert systems with the aid of the modeldriven development approach

机译:借助模型驱动的开发方法设计基于规则的专家系统

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The problem of improving the efficiency of designing process of knowledge bases and expert systems remains a relevant issue. The effectiveness of this process can be improved by using the principles of conceptual (cognitive) modelling and generative programming-based approaches, in particular, a model-driven development. This paper describes implementation and application of the model-driven development approach for the design of rule-based expert systems and knowledge bases. The implementation proposed takes into account peculiarities of the intelligent systems development process, such as stages of conceptualization and formalization, and provides the practical use of ontologies and conceptual models as computation-independent and subject domain models. An extension of UML, namely, the Rule Visual Modelling Language is used to represent logical rules and create platform-independent and platform-specific models. Rule Visual Modelling Language elements ensure that some features of a programming language for knowledge bases, for example, CLIPS, are taken into account. Therefore, CLIPS and the Personal Knowledge Base Designer are used as the targeted platforms for generation of source codes and specifications. The applicability of the approach is demonstrated by a case study: development of the knowledge base and expert system for identification of the causes of damages and destruction of construction materials in petrochemistry.
机译:提高知识库和专家系统的设计过程效率的问题仍然是一个相关问题。通过使用概念(认知)建模和基于生成编程的方法(尤其是模型驱动的开发)的原理,可以提高此过程的有效性。本文介绍了模型驱动的开发方法在基于规则的专家系统和知识库的设计中的实现和应用。提出的实现考虑了智能系统开发过程的特殊性,例如概念化和形式化阶段,并提供了本体和概念模型作为计算独立和主题领域模型的实际使用。 UML的扩展,即规则视觉建模语言,用于表示逻辑规则并创建独立于平台和特定于平台的模型。规则视觉建模语言元素可确保考虑用于知识库的编程语言的某些功能,例如CLIPS。因此,CLIPS和个人知识库设计器用作生成源代码和规范的目标平台。案例研究证明了该方法的适用性:开发知识库和专家系统以识别石化中建筑材料的损坏和破坏原因。

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