• Journal of Biosystems Engineering
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• 제22권3호
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• pp.343-350
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• 1997

In farm management, many factors should be considered to select optimum farm machinery Some factors such as fm size can be quantified, but other factors such as working experience can not be. Futhermore, as several factors are missed and assumptions are made for the selection using conventional computer programs, the result is sometimes questionable. This problem can be solved using artificial intelligent techniques such as expert system. In this study, an expert system was developed to select optimum machinery by considering available working days, machinery to on, farming environments, labor cost, population, etc. It also took into account the characteristics of machinery, turning radius, easiness of operation, subsidy, loan to purchase, asset. farmers age, Rest Metabolic Rate, and working experience, etc. Expertise and experience of human experts were utilized to develop the expert system. The developed expert system was evaluated by the human experts and others, and it was proved to be practically useful fir farmers.

• 한국조명전기설비학회지:조명전기설비
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• 제8권1호
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• pp.46-52
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• 1994

본 연구에서는 최근 많은 관심이 되고 이는 퍼지제어 알고리즘을 이용하여 유도 전동기 가변속 운전을 실현하였다. 퍼지 제어기는 전문가의 지식이나 경험에 기초로 하여 설계되기 때문에 안전한 제어 성능을 기대하기는 어렵다. 따라서, 견실한 퍼지 제어기 설계를 위하여 최적스케일 팩터 선정법을 제안하였다. 실험 결과, 퍼지 제어기의 제어 성능 및 외란 특성이 종래의 PI제어기에 비하여 우수함을 입증하였다.