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홍철의,김영준,Hong, Cheol-Ui,Kim, Yeong-Jun 한국정보처리학회 2000 정보처리논문지 Vol.7 No.4
This paper proposes new cost error measurement method and analyzes the optimistic and pessimistic cost errors statistically which is resulted from an asynchronous parallel Simulated annealing (SA) in distributed memory multicomputers. The traditional cost error measurement scheme has inherent problems which are corrected in the new method. At each temperature the new method predicts the amount of cost error that an algorithm will tolerate and still converge by the hill-climbing nature of SA. This method also explains three interesting phenomenon of he cost error analytically. So the new cost error measurement method provides a single mechanism for the occurrence of cost error and its control.
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유전학 기반 학습 환경하에서 분류 시스템의 성능 향상을 위한 엔-버전 학습법
김영준,홍철의,Kim, Yeong-Jun,Hong, Cheol-Ui 한국정보처리학회 1999 정보처리논문지 Vol.6 No.7
델보는 주어진 사례의 집합으로부터 이들 사례들을 분류할 수 있는 베이지안 분류 규칙들로 이루어진 규칙 집합을 습득하는 유전학 기반 귀납적 학습 시스템이다. 규칙 집합의 습득과정에서 델보가 당면하게 되는 한 가지 문제점은 학습 과정이 최적의 규칙 집합이 아닌 지역 최적치를 습득하고 종료하는 경우가 가끔 발생한다는 것이다. 다른 하나의 문제점은 훈련 사례에 대한 경우와는 달리 새로운 평가 사례에 대해 분류 성능이 현저히 저하되는 규칙 집합을 습득하는 경우가 가끔 발생한다는 것이다. 본 논문에서는 이러한 문제점을 해결하여 보다 성능이 향상된 분류 시스템을 구축하기 위한 기법으로 엔-버전 시스템을 구축함으로써 분류 시스템의 전체적인 성능을 향상시키는 기법이다. 엔-버전 학습법의 구현을 위해 다수의 규칙 집합을 이용하여 최종 분류 결과를 도출해 내기 위한 기법과 습득된 규칙 합들로부터 분류 시스템을 구축하기 위한 최적의 규칙 집합의 조합을 찾기 위한 기법을 제시하고 다수의 사례 집합을 이용하여 엔-버전 학습법이 델보의 학습 환경에 미치는 영향을 평가하였다. DELVAUX is a genetics-based inductive learning system that learns a rule-set, which consists of Bayesian classification rules, from sets of examples for classification tasks. One problem that DELVAUX faces in the rule-set learning process is that, occasionally, the learning process ends with a local optimum without finding the best rule-set. Another problem is that, occasionally, the learning process ends with a rule-set that performs well for the training examples but not for the unknown testing examples. This paper describes efforts to alleviate these two problems centering on the N-version learning approach, in which multiple rule-sets are learning and a classification system is constructed with those learned rule-sets to improve the overall performance of a classification system. For the implementation of the N-version learning approach, we propose a decision-making scheme that can draw a decision using multiple rule-sets and a genetic algorithm approach to find a good combination of rule-sets from a set of learned rule-sets. We also present empirical results that evaluate the effect of the N-version learning approach in the DELVAUX learning environment.
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합류식 하수관거 지역에서 강우시 하수처리장 적정운영방안에 관한 연구
이두진 ( Lee Du Jin ),신응배 ( Sin Eung Bae ),홍철의 ( Hong Cheol Ui ),안세영 ( An Se Yeong ) 한국물환경학회 2004 한국물환경학회지 Vol.20 No.2
The purpose of this study was to evaluate alternatives for stable operation of WWTP(Wastewater Treatment Plant) with a higher rate of inflows and a higher concentration of pollutants during wet weather to minimize the pollution loads being discharged into receiving waters. 3Q(Q: dry weather flow) of a base flow is normally intercepted and flows into WWTP as it was current practice. It is revealed by simulation that the bypassing alternative of 1Q through secondary treatment and 2Q into the stream after primary treatment was as good as it is expected. The bypass pollution loads were in the range of 23.9 - 38.5% of the total loads flowing into the WWTP indicating that the bypassed flows need an extra treatment such as stormwater detention reservoir, high-rate coagulation with sedimentation, and step-feed. The high-rate coagulation with sedimentation was the most effective with respect to removal of the pollution loads.
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김장윤(Kim Jang Yun),현동훈(Hyun Dong Hoon),홍철의(Hong Cheol Ui) 한국생산제조학회 2015 한국생산제조학회지 Vol.24 No.2
In this paper, the performance of a system was analyzed according to the design parameters of a LED secondary lens that can be applied at a very close range, e.g., for direct lighting or display systems. We designed the secondary lens of the very-close-range LED using an aspheric equation and analyzed its performance―particularly the angle of the beam spread, central luminous intensity, and light uniformity―with respect to the thickness of lens, radius, conic constant, and asphericity (4th). Our analysis shows that four parameters affect the performance. The simulation results indicate an optimal thickness of 1 mm and show that a larger radius yields higher performance. The optimal range for the conic constant was determined as -1.21 to -1.25, the optimal range for the asphericity was determined as 0.0047xx to 0.0049xx (4th).
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