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Study on Knowledge Expression Methods and Reasoning Strategies in Intelligent CAD System

机译:智能CAD系统的知识表达方法与推理策略研究

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摘要

As the core of intelligent computer aided design (ICAD), the expert system with the purpose of product design automation and intelligence has been developed rapidly. Knowledge expression, management, utilization, and access method has always been the core of artificial intelligence and expert system technology , Substantial literature both at home and abroad involved in the content and achieved certain results in the area of design. In the aspect of knowledge expression and management, including: the knowledge expression based on gene model[3], the knowledge expression based on design pattern[4], the knowledge expression based on Petri net, mixed knowledge expression, and so on. In the aspect of system reasoning, including: fuzzy reasoning[5,6], cease-based reasoning[7], integration reasoning, and so on. This paper mainly introduces some technologies and methods about electrical products at ICAD system with the above-mentioned two aspects. As a sub-system of ICAD system, the expert system for electrical apparatus designing was studied in the artificial intelligent technologies, including the way to build a large knowledge database managed by multi level frames and expressed by various knowledge expression methods, and the reasoning strategy suitable for the structure of knowledge database and integrated rule-based reasoning (RBR) with case-based reasoning (CBR) together. Based on these technologies, two-level expert system controlled by meta reasoning machine was built so that the reasoning efficiency was boosted very strongly.
机译:作为智能计算机辅助设计(ICAD)的核心,以产品设计自动化和智能化为目的的专家系统得到了快速发展。知识的表达,管理,利用和访问方法一直是人工智能和专家系统技术的核心,国内外大量文献参与其中,并在设计领域取得了一定成果。在知识表达和管理方面,包括:基于基因模型的知识表达[3],基于设计模式的知识表达[4],基于Petri网的知识表达,混合知识表达等。在系统推理方面,包括:模糊推理[5,6],基于停止的推理[7],集成推理等。本文主要从上述两个方面介绍ICAD系统中有关电气产品的一些技术和方法。作为ICAD系统的子系统,以人工智能技术研究了电气设备设计专家系统,包括建立由多级框架管理并以各种知识表示方法表示的大型知识数据库的方法以及推理策略。适用于知识数据库的结构,并将基于规则的推理(RBR)与基于案例的推理(CBR)集成在一起。基于这些技术,构建了由元推理机控制的二级专家系统,极大地提高了推理效率。

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