의사결정트리 기법을 이용한 터널 보조공법 선정방안 연구

A Study on the Effective Selection of Tunnel Reinforcement Methods using Decision Tree Technique

초록

The auxiliary reinforcement method is normally applied to prevent a possible collapse of the tunnel face where the ground condition is not favorable or geologic information is not sufficient. Recently, several engineering approaches have been made to choose the effective reinforcement methods using expert system such as neural network and fuzzy theory field, among others. Even if the expert system has offered many decision aid tools to properly select the reinforcement method, the quantitative assessment items are not easy to estimate and this is why the data mining technique, widely used in the field of social science, medical treatment, banking and agriculture, is introduced in this study. Using decision tree together with PDA, the decision aids for reinforcement method based on field construction data are created to derive the field rules and future study will be concentrated on the application of the proposed methods in a variety of underground development cases.

키워드

Data mining; decision tree; tunnel; reinforcement method; PDA 요 지터널 시공시 지반상황이 불량하거나 불확실한 지질정보로 인한 붕락사고를 방지하기 위하여 지보재와 병용하여 터널보조공법을 사용한다. 현재 보조공법에 관련된 전문가 시스템은 인공신경망; 퍼지추론 등의 연구가 진행되었고 터널 기술자에게 보조공법을 결정하는데 많은 도움을 주고 있는 상황이나 보조공법을 결정하는데 있어 정량적인 평가항목; 데이터 마이닝; 의사결정트리; 터널; 보조공법; PDA
제목
의사결정트리 기법을 이용한 터널 보조공법 선정방안 연구
제목 (타언어)
A Study on the Effective Selection of Tunnel Reinforcement Methods using Decision Tree Technique
저자
김종규; 사공명; 이준석; 이용주
발행일
2006-07
저널명
대한토목학회논문집(국문)
권
26
호
4-C
페이지
255 ~ 264