RBFN기법을 활용한 적응적 사례기반 설계

  • 정사범 (LG전자생산기술원 디자인엔지니어링그룹) ;
  • 임태수 (성결대학교 컴퓨터공학부)
  • 발행 : 2005.10.29

초록

This paper describer a design expert system which determines the design values of shadow mask using Case-Based Reasoning. In Case-Based Reasoning, it is important to both retrieve similar cases and adapt the cases to meet the design specifications exactly. Especially, the difficulty in automating the adaptation process will prevent the designers from using the design expert systems efficiently and easily. This paper explains knowledge-based design support systems for shadow mask through neural network-based case adaptation. Specifically, we developed 1) representing design knowledge and 2) adaptive case-based reasoning method using RBFN (Radial Basis Function Network).

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