• 산업경영시스템학회지
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• 제40권2호
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• pp.129-136
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• 2017

Among the information technology and automation that have rapidly developed in the manufacturing industries recently, tens of thousands of quality variables are estimated and categorized in database every day. The former existing statistical methods, or variable selection and interpretation by experts, place limits on proper judgment. Accordingly, various data mining methods, including decision tree analysis, have been developed in recent years. Cart and C5.0 are representative algorithms for decision tree analysis, but these algorithms have limits in defining the tolerance of continuous explanatory variables. Also, target variables are restricted by the information that indicates only the quality of the products like the rate of defective products. Therefore it is essential to develop an algorithm that improves upon Cart and C5.0 and allows access to new quality information such as loss cost. In this study, a new algorithm was developed not only to find the major variables which minimize the target variable, loss cost, but also to overcome the limits of Cart and C5.0. The new algorithm is one that defines tolerance of variables systematically by adopting 3 categories of the continuous explanatory variables. The characteristics of larger-the-better was presumed in the environment of programming R to compare the performance among the new algorithm and existing ones, and 10 simulations were performed with 1,000 data sets for each variable. The performance of the new algorithm was verified through a mean test of loss cost. As a result of the verification show, the new algorithm found that the tolerance of continuous explanatory variables lowered loss cost more than existing ones in the larger is better characteristics. In a conclusion, the new algorithm could be used to find the tolerance of continuous explanatory variables to minimize the loss in the process taking into account the loss cost of the products.

• 농업생명과학연구
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• 제50권3호
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• pp.69-80
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• 2016

본 연구는 산겨릅나무 자생지(화악산, 망대암산, 계방산, 고루포기봉, 가리왕산, 두위봉, 금대봉과 지리산)의 입지환경, 토양특성, 및 식생구조 분석을 통해 자생지 보전 및 복원을 위한 기초자료를 제공하고자 하였다. 산겨릅나무 자생지는 해발 605~1,413m에 위치하고, 경사는 8~30°로 다양하며, 노암율은 8~50%로 나타났다. PC-ORD를 이용한 이단계 군집분석 결과 군집I(산겨릅나무-신갈나무 군집), 군집II(산겨릅나무-까치박달 군집), 군집III(신갈나무-피나무 군집) 등 3개의 식물 군집으로 구분되었다. 종다양성지수(H')는 군집 II가 1.474로 가장 높게 나타났으며, 군집 I이 1.417, 군집 III이 1.219로 확인되었다. 산겨릅나무 자생지의 토성은 점토의 비율이 높은 식양토이며, 토양 산도, 유기물함량, 유효인산은 각각 pH 4.8, 15.56%, 2.33ppm으로 확인되었다. 토양 특성과 군집, 표징종을 ordination분석한 결과 가장 크게 영향을 주는 인자는 사면경사이며, 아교목층과 관목층의 피도, 유기물함량, 전질소, 칼슘, 마그네슘인 것으로 확인되었다. 환경요인 간 상관 분석을 실시한 결과, O.M. - (T.N., K+, Mg2+, CEC, EC), T.N. - (K+, Mg2+, CEC, EC) 등은 높은 정의 상관관계를 형성하였다.