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A Rough Set based Knowledge Discovery Model and its Application in Virtual Assembly

机译:基于粗糙集的知识发现模型及其在虚拟装配中的应用

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摘要

To solve the problem of lack of assemble knowledge in ship virtual assembly system, a novel rough-set theory based knowledge discovery model is studied to find the process knowledge hidden in virtual assembly. First the typical knowledge structure used in ship virtual assembly is analyzed and improved into a generalized definition using the object-oriented technology. The technology solution to develop knowledge discovery model for ship virtual assembly is proposed based on rough set theory. All the key technologies such as Petri-RS information transformation model, RS attribute reduction and knowledge management technologies are analyzed respectively for real engineering application. The developed knowledge discovery system of the ship virtual assembly can realize the data processing and mining, to discover useful assembly knowledge automatically. Further with an engineering example from virtual assembly in shipbuilding enterprises, this paper provides a technical solution to disvover useful assembly knowlege, reduce assembly time for ship building in real product line, to enhance production efficiency obviously.
机译:为了解决船舶虚拟装配系统中缺乏组装知识的问题,研究了一种新颖的基于粗糙的理论基于知识发现模型,以找到隐藏在虚拟装配中的过程知识。首先,使用面向对象技术分析和改进船舶虚拟组件中使用的典型知识结构。基于粗糙集理论,提出了为船舶虚拟组件开发知识发现模型的技术解决方案。分别分析了Petri-RS信息转换模型,RS属性减少和知识管理技术等所有关键技术,以进行实际工程应用。发达的船舶虚拟组件的知识发现系统可以实现数据处理和挖掘,以自动发现有用的装配知识。此外,在造船企业中的虚拟组件中,本文提供了一种技术解决方案,以减少有用的装配知识,减少现实产品线上船舶建筑的装配时间,显然提高了生产效率。

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