• 대한수학회지
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• 제41권6호
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• pp.957-976
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• 2004

It is well known that the application of the nonlinear coordinate transformations is useful for efficient numerical evaluation of weakly singular integrals. In this paper, we consider the trapezoidal rule combined with a nonlinear transformation $\Omega$$_{m}$(b;$\chi$), containing a parameter b, proposed first by Yun [14]. It is shown that the trapezoidal rule with the transformation $\Omega$$_{m}$(b;$\chi$), like the case of the Gauss-Legendre quadrature rule, can improve the asymptotic truncation error by using a moderately large b. By several examples, we compare the numerical results of the present method with those of some existing methods. This shows the superiority of the transformation $\Omega$$_{m}$(b;$\chi$).TEX>).

• 한국지능시스템학회논문지
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• 제20권1호
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• pp.30-35
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• 2010

본 논문에서는 대칭 로지스틱 함수에 기반을 둔 히스토그램 평활화를 이용한 영상의 화질개선을 제안하였다. 여기서 히스토그램 평활화는 영상의 명암도를 조정하여 화질을 개선하는 간단하고 효과적인 공간영역 기반 처리기법이다. 또한 대칭 로지스틱 함수는 s-자 형의 비선형 변환함수로 영상의 명암도 발생빈도수에 따라 밝기개선 정도를 비선형적으로 조정하기 위함이다. 특히 영상의 히스토그램에서 최대 발생빈도수를 가지는 명암도와 전체 픽셀수만을 이용한 유연한 대칭의 로지스틱 함수를 제안함으로써, 기존 로지스틱 함수에서의 지수함수 계산 부담을 감소시켰다. 제안된 평활화 기법을 크기와 히스토그램 분포가 다른 5개의 영상을 대상으로 실험한 결과, 원 영상이나 기존의 전역 히스토그램 평활화의 결과영상보다 우수한 화질개선 성능이 있음을 확인하였다.

• 한국태양에너지학회 논문집
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• 제39권6호
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• pp.113-125
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• 2019

With the opening of the small power brokerage business market in December 2018, the small power trading market has started in Korea. Operators must submit the day-ahead estimates of power output and receive incentives based on its accuracy. Therefore, the accuracy of power generation forecasts is directly affects profits of the operators. The forecasting process for power generation can be divided into two procedure. The first is to forecast solar irradiation and the second is to transform forecasted solar irradiation into power generation. There are two methods for transformation. One is to simulate with physical model, and another is to use regression model. In this study, we found the best-fit regression model by analyzing hourly data of PV output and solar irradiation data during three years for 242 PV plants in Korea. The best model was not a linear model, but a sigmoidal model and specifically a Gompertz model. The combined linear regression and Gompertz curve was proposed because a the curve has non-zero y-intercept. As the result, R² and RMSE between observed data and the curve was significantly reduced.