서지주요정보
의사결정나무를 이용한 공정모니터링 데이터 분석에 관한 연구 = Analysis of process monitoring data using decision trees
서명 / 저자 의사결정나무를 이용한 공정모니터링 데이터 분석에 관한 연구 = Analysis of process monitoring data using decision trees / 김성준.
발행사항 [대전 : 한국과학기술원, 2001].
Online Access 원문보기 원문인쇄

소장정보

등록번호

8011744

소장위치/청구기호

학술문화관(문화관) 보존서고

MIE 01003

휴대폰 전송

도서상태

이용가능

대출가능

반납예정일

등록번호

9007550

소장위치/청구기호

서울 학위논문 서가

MIE 01003 c. 2

휴대폰 전송

도서상태

이용가능

대출가능

반납예정일

리뷰정보

초록정보

This thesis deals with a decision tree approach for analyzing the process monitoring data. Decision tree is a data mining technique and has been widely used for the purpose of classification. Decision tree is also useful in analyzing the training data which may contain disturbances. The existing data mining techniques conduct a binary split of a continuous-valued attribute for discretization. This form of classification is very fast and easy to interpret. However, the binary split has a problem in analyzing process monitoring data in that it is difficult to determine process parameter`s upper and lower specification limit at the same time. In addition, usual decision tree analysis techniques have focused on a single performance characteristic. However, multiple performance characteristics appear more commonly in the process monitoring data. Therefore, a new approach is necessary to analyze multiple performance characteristics simultaneously. In this thesis, a decision tree technique with ternary split at each node is developed for finding principal process parameters which influence the performance characteristic. The developed method can be used to determine the specification limits of the process parameters in both cases of single and multiple performance characteristics.

서지기타정보

서지기타정보
청구기호 {MIE 01003
형태사항 v, 94 p. : 삽도 ; 26 cm
언어 한국어
일반주기 저자명의 영문표기 : Sung-Jun Kim
지도교수의 한글표기 : 염봉진
지도교수의 영문표기 : Bong-Jin Yum
학위논문 학위논문(석사) - 한국과학기술원 : 산업공학과,
서지주기 참고문헌 : p. 92-94
주제 공정 모니터링 데이터
의사결정나무
Process monitoring data
Decision trees
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