친자 및 혈연관계 분석시스템의 성능을 개선하기 위한 지식기반 전문가 시스템 개발

• 영문명: Development of a Knowledge-based Expert System to Improve the Performance of the Paternity and Kinship Analysis System
• 발행기관: 한국산업경영시스템학회
• 저자명: 구교찬(Kyo-Chan Koo) 김선욱(Sun-Uk Kim)
• 간행물 정보: 『한국산업경영시스템학회 학술대회』2015년 추계학술대회 논문집, 123~129쪽, 전체 7쪽
• 주제분류: 공학 > 산업공학
• 파일형태: PDF
• 발행일자: 2015.10.31

영문 초록

This paper considers a paternity and kinship analysis system(PKAS) being currently used in real sites. A knowledge-based expert system is proposed to improve the performance of PKAS in terms of accuracy, speed, training time, and satisfaction, which are common measures for evaluation. The knowledge base, one of the most important components in the knowledge-based expert system(KBES), consists of a rule made from random matching algorithm, decision rules of allele types and guide rules of options. The last two rules are learning incrementally from sample data. The results show that PKAS armed with the expert system ensures the better performance with regard to these criteria than the existing system. Especially as far as speed is concerned, as the sample size increases, it outperforms the existing one. As the number of samples increases, while processing time increases nearly exponentially in the existing PKAS, it does linearly in our proposed system.

목차

1. 서론

2. 연구방법

3. 연구결과

4. 결론

키워드

Knowledge-Based Expert System Paternity analysis Kinship analysis Short Tandem Repeat