• 한국수자원학회논문집
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• 제44권8호
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• pp.619-628
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• 2011

본 연구의 목적은 월강우량을 이용하여 강우침식인자를 추정하는 기존의 방법인, Fournier 지수, modified Fournier 지수, IAS (Institute of Agricultural Sciences) 지수 등의 적용성을 확인하고 더 합리적인 월강우량 기반의 강우침식인자 추정모델을 제시하기 위한 것이다. 본 연구에서는 월강우량 기반의 수정 IAS 지수를 새롭게 제안하였다. 이것은 연중가장 비가 많이 내린 두 달의 강우량의 합으로써 강우침식인자를 추정하는 기존의 IAS 지수의 개념을 확장한 것이다. 본 연구에서는 25년 이상의 21개 지점에 대한 월강우량 및 연 강우침식인자를 토대로 각 추정방법에 대한 상관분석 및 회귀분석을 실시하였다. 그 결과 수정IAS 지수가 기존의 연강수량 및 월강우량을 이용한 추정방법 보다 우리나라 중서부 및 남서부 지역의 강우침식인자의 변동을 잘 나타내는 합리적인 지표임을 알 수 있었다.

• Structural Engineering and Mechanics
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• 제35권4호
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• pp.431-457
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• 2010

This article provides a discussion of the mathematic modeling of connections for designing and qualifying structures, systems, and components subject to monotonic or cyclic loading. To characterize the force-deformation behavior of connections under monotonic loading, a review of the Ramberg-Osgood, Richard-Abbott, and Menegotto-Pinto models is conducted, and it is shown that these nonlinear functions can be mathematically derived by scaling up or down a linear force-deformation function. A generalized four-parameter model for simulating connection behavior is investigated to facilitate nonlinear regression analysis. In order to perform seismic analysis of frameworks, a hysteretic model accounting for loading, unloading, and reloading is described using the established monotonic model. For preliminary analysis, a method is provided to quickly determine the model parameters that fit approximately with the observed data. To reach more accurate values of the parameters, the methods of nonlinear regression analysis are investigated and the modified Levenberg-Marquardt and separable nonlinear least-square algorithms are applied in determining the model parameters. Example case studies illustrate the procedure for the computation through the use of experimental/analytical data taken form the literature. Transformation of connection curves from the three-parameter model to the four-parameter model for structural analysis is conducted based on the modeling of connections subject to fire.

• 대한교통학회지
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• 제29권2호
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• pp.15-24
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• 2011

본 연구에서는 현행 버스서비스 평가체계를 보완하기 위해 유익투입물을 고려한 수정 BCC 모형을 이용하여 2009년 서울시 179개 지선버스노선의 형평성을 분석하였다. 분석대상은 정류장 수와 운행횟수를 사용하여 형평성 지표와 접근성 지표를 산출하는 형태로 상정하였다. 투입지향 수정 BCC 모형으로 분석한 결과 전체 분석대상 중 약 9%의 노선만이 형평적인 것으로 나타났으며, 평균 형평성 추정치는 0.702인 것으로 분석되었다. 또한 서울시 지선버스노선은 형평성을 개선하기 위해 정류장 수와 운행횟수를 평균적으로 약 60% 이상 증가시킬 수 있는 것으로 나타났다. 토빗회귀분석을 수행하여 분석대상의 형평성에 영향을 미치는 결정요인을 분석한 결과 정류장 수와 운행횟수는 모두 5% 유의수준에서 통계적인 유의미성을 확보하였으며, 정류장 수가 영향력이 가장 큰 결정요인으로 분석되었다.

• 한국축산식품학회지
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• 제32권6호
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• pp.783-788
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• 2012

The aim of this study was to optimize the manufacturing condition of spreadable modified butter by RSM. Based on the central composite design, the degree of optimization was expressed as a SFC as a dependent variable (Y, %) determined by NMR with 23 experimental groups. Three independent variables were the contents of butter ($X_1$, 35-75%), the contents of grape seed oil ($X_2$, 15-35%), and the contents of hydrogenated soybean oil ($X_3$, 0-4%). As the result, SFC at $10^{\circ}C$ was ranged from 32.37 to 42.76%. In addition, the regression coefficients were calculated for SFC at $10^{\circ}C$ by RSREG. The regression model equation for the SFC was $Y=39.18-0.04X_1X_3$. Consequently, the optimal contents for manufacturing spreadable modified butter were determined as 55.18% for butter, 40.78% for grape seed oil, and 4.08% for hydrogenated soybean oil, respectively. The predicted response value for SFC at $10^{\circ}C$ was 30.20%, comparable to the actual experimental SFC value as 29.85%. Finally hardness and spreadability in reference butter and spreadable modified butter produced under the optimal conditions was measured. The hardness in spreadable modified butter was 31.80 N as compared to 69.92 N in reference butter. The spreadability in spreadable modified butter was 5.6 point as compared to reference butter. This difference may be due to the contents of solid fat by butter and hydrogenated soybean oil. This study showed that the SFC value at $10^{\circ}C$ could be a suitable indicator for the manufacturing spreadable modified butter to predict important attributes such as mouth feel, hardness and spreadability.

• Communications for Statistical Applications and Methods
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• 제7권2호
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• pp.605-616
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• 2000

Three primary interests frequently raised by mortgage companies are introduced and the corresponding statistical approaches for the default probability in mortgage companies are examined. Statistical models considered in this paper are time series, logistic regression, decision tree, neural network, and discrete time models. Usage of the models is illustrated using an artificially modified data set and the corresponding models are evaluated in appropriate manners.

• 제어로봇시스템학회논문지
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• 제15권1호
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• pp.44-53
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• 2009

In this paper, Recursive Least Squares (RLS) and Fourier Transform Regression (FTR) methods for estimating stability and control derivatives of small unmanned helicopter are evaluated together with MMLE technique. Flight data simulated by using a commercial small-scale helicopter model are exploited to estimate the parameters with accuracies for hover and cruise modes. The performances of the system identification methods are also compared by analyzing the responses of the reconstructed systems using estimated derivatives.

• Journal of the Korean Statistical Society
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• 제28권2호
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• pp.195-210
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• 1999

We consider a large class of exponential regression models with censored data and propose two modified Fisher scoring methods with corresponding algorithms. These proposed methods improve the Newton-Raphson method in estimating the model parameters. The simulated and real examples are illustrated in aspect of convergence.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2001년도 학술발표회 논문집(I)
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• pp.45-51
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• 2001

The daily inflow is apparently one of nonlinear and complicated phenomena. The nonlinear and complexity make it difficult to model the prediction of daily flow, but attractive to try the neural networks approach which contains inherently nonlinear schemes. The study focuses on developing the forecasting models of daily inflows to a large dam site using neural networks. In order to reduce the error caused by high or low outliers, the back propagation algorithm which is one of neural network structures is modified by combining a regression algorithm. The study indicates that continuous forecasting of a reservoir inflow in real time is possible through the use of modified neural network models. The positive effect of the modification using tole regression scheme in BP algorithm is showed in the low and high ends of inflows.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.130-133
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• 2000

In this paper, a new design methodology named FNNN(Fuzzy Polynomial Neural Network) algorithm is proposed to identify the structure and parameters of fuzzy model using PNN(Polynomial Neural Network) structure and a fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Handling), and uses several types of polynomials such as linear, quadratic and modified quadratic besides the biquadratic polynomial used in the GMDH. The premise of fuzzy inference rules defines by triangular and gaussian type membership function. The fuzzy inference method uses simplified and regression polynomial inference method which is based on the consequence of fuzzy rule expressed with a polynomial such as linear, quadratic and modified quadratic equation are used. Each node of the FPNN is defined as fuzzy rules and its structure is a kind of neuro-fuzzy architecture Several numerical example are used to evaluate the performance of out proposed model. Also we used the training data and testing data set to obtain a balance between the approximation and generalization of proposed model.

• Journal of Biosystems Engineering
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• 제25권1호
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• pp.47-54
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• 2000

This study was performed to determine desorption equilibrium moisture contents of rough rice, brown rice, white rice and rice hull grown in Korea. EMC values were measured by static method using saturated salt solutions at three temperature levels of 2$0^{\circ}C$, 3$0^{\circ}C$ and 4$0^{\circ}C$ and eight relative humidity levels in the range from 11.2% to 85.0%. The measured EMC values were fitted to modified Henderson, Chung-Pfost , and modified Oswin models by using nonlinear regression analysis. The results of comparing root mean square errors for three models showed that modified Henderson and CHung -Pfost models could serve as good models, and that modified Oswin model could not be available for rough rice, brown rice, white rice and rice hull.