• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.63-68
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• 1998

This paper proposes fuzzy regression analysis with non-symmetric fuzzy coefficients. By assuming non-symmetric triangular fuzzy coefficients and applying the quadratic programming fomulation, the center of the obtained fuzzy regression model attains more central tendency compared to the one with symmetric triangular fuzzy coefficients. For a data set composed of crisp inputs-fuzzy outputs, two approximation models called an upper approximation model and a lower approximation model are considered as the regression models. Thus, we also propose an integrated quadratic programming problem by which the upper approximation model always includes the lower approximation model at any threshold level under the assumption of the same centers in the two approximation models. Sensitivities of Weight coefficients in the proposed quadratic programming approaches are investigated through real data.

• Journal of the Korean Data and Information Science Society
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• 제15권2호
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• pp.449-455
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• 2004

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval regression models for crisp input-output data. The proposed method is based on quadratic loss SVM, which implements quadratic programming approach giving more diverse spread coefficients than a linear programming one. The proposed algorithm here is model-free method in the sense that we do not have to assume the underlying model function. Experimental result is then presented which indicate the performance of this algorithm.

• 한국항해항만학회지
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• 제30권7호
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• pp.561-566
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• 2006

In this paper, we propose a new ship scheduling set packing model considering limited risk or variance. The set packing model is used in many applications, such as vehicle routing, crew scheduling, ship scheduling, cutting stock and so on. As long as the ship scheduling is concerned, there exits many unknown external factors such as machine breakdown, climate change and transportation cost fluctuation. However, existing ship scheduling models have not considered those factors apparently. We use a quadratic set packing model to limit the variance of expected cost of ship scheduling problems under stochastic spot rates. Set problems are NP-complete, and additional quadratic constraint makes the problems much harder. We implement Kelley's cutting plane method to replace the hard quadratic constraint by many linear constrains and use branch-and-bound algorithm to get the optimal integral solution. Some meaningful computational results and comments are provided.

• 한국방사선학회논문지
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• 제9권6호
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• pp.417-420
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• 2015

본 연구는 탄소 빔의 분할조사 후 세포생존율 (Surviving Fraction, SF) 값에 따른 Linear-Quadratic model, Incomplete Repair model, Marchese model의 결과값을 비교하기 위해 진행하였다. 탄소 빔을 4fraction까지 조사한 후 얻은 세포생존율 값을 바탕으로 mathematica 프로그램 (ver 9.0)을 이용하여 각각의 모델로 결과값을 얻어 비교해 보았다. 그 결과 즉시 NB1RGB를 시딩한 값은 repair가 감안되지 않은 LQ 모델이 적합하였지만 fraction 시행한 후의 결과값은 오차를 보였다. 따라서 Potentially Lethal Damage Repair (PLDR)과 Sublethal Damage Repair (SLDR)의 발생을 각각 감안한 repair 모델을 이용하여 적합한지 판단하였다. 이를 바탕으로 탄소 빔의 분할 조사 시 LQ 모델에 각각의 repair의 양을 감안한 새로운 회복 관련 모델의 적용 가능성을 보고자 하였다.

• International Journal of Reliability and Applications
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• 제12권1호
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• pp.1-14
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• 2011

This paper discusses the stochastic analysis and the statistical inference of a quadratic failure rate semi-Markov reliability model. Maximum likelihood procedure will be used to obtain the estimators of the parameters included in this reliability model. Based on the assumption that the lifetime and repair time of the system units are random variables with quadratic failure rate, the reliability function of this system is obtained. Also, the distribution of the first passage time of this system is derived. Many important special cases are discussed.

• Communications for Statistical Applications and Methods
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• 제9권1호
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• pp.229-240
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• 2002

Whether to use linear or quadratic model in the analysis of regression data is one of the important problems in classical regression model and measurement error model (MEM). In MEM, four goodness of fit test statistics are available In solving that problem. Two are from the derivation of estimators of quadratic MEM, and one is from that of the general $k^{th}$-order polynomial MEM. The fourth one is derived as a variation of goodness of fit test statistic used in linear MEM. The purpose of this paper is to find the most powerful test statistic among them through the small-scale simulation.

• Journal of Radiation Protection and Research
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• 제17권1호
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• pp.21-30
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• 1992

KCCH cyclotron neutron(30cCy/min) 및 $^{60}Co\;{\gamma}-ray(210cGy/min)$를 시험관내의 정상인체 말초혈액임파구에 조사하여 염색체이상(dicentric 및 centric ring)을 관찰하고 이의 선량-반응관계식을 linear model$(Y=K_1D+a)$, power-law model$(Y=K_2D^n)$, quadratic model$(Y=K_3D^2)$ 및 linear-quadratic model$(Y={\alpha}D+{\beta}D^2)$을 사용하여 구하고 이들 model중 염색체이상의 측정치와 가장 일치하는 관계식을 근거로 하여 ${\gamma}-ray$에 대한 neutron의 relative biological effectiveness (RBE)를 산출하였다. 염색체 이상(dicentric plus centric ring)의 발생분포는 ${\gamma}-ray$의 경우 linear model(P=0.067)을 제외한 power-law model$[Y=(5.81{\pm}1.96){\times}10^6D^{1.93+0.06},\;P=0.931]$, quadratic model$[Y=(3.91{\pm}0.09){\times}10^{-6}D^2,\;P=0.972]$ 및 linear-quadratic model $[Y=(6.55{\pm}6.83){\times}10^{-5}D+(3.72{\pm}0.22){\times}10^{-6}D^2$ P=0.922]에 적합하였다 neutron의 경우 linear model $(Y=(6.12{\pm}0.17){\times}10^{-3}\;D-0.22,\;P=0.987]$에 가장 일치하였고 quadratic model (P<0.005)을 제외한 power-law model $[Y=(5.36{\pm}3.02) {\times}10^{-4}D^{1.42+0.11},\;P=0.601]$ 및 linear-quadratic model $[Y=(2.43{\pm}0.70){\times}10^{-3}D+(1.21{\pm}0.39){\times}10^{-7}D^2,\;P=0.415]$에 비교적 적합하였다. 세포당 0.1-1.5개의 염색체이상을 나타내는 neutron의 ${\gamma}-ray$에 대한 RBE는 $2.714{\pm}0.408$이었다.

• 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.

• 한국토양비료학회지
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• 제43권2호
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• pp.174-179
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• 2010

본 연구에서는 사탕무의 시비반응을 합리적으로 해석하고 경제성 있는 최적 시비량 및 최대 수확량의 도출을 위한 방법을 검토하기 위하여 간척지 토양에서 수준별 질소비료와 돈분퇴비의 시용에 따른 사탕무의 시비반응을 조사하였다. 시비반응은 Quadratic model, Exponential model, Square root model 및 Linear response & plateau model을 이용하여 통계적으로 분석하였다. 토양 EC가 증가함에 따라 사탕무 지하부 생체중이 지수함수적으로 감소하였다. 질소비료 시비수준별 사탕무 지하부 생체량의 시비반응은 Linear response에서 결정계수 & plateau model ($R^2$)가 $0.92^{**}$로 고도의 통계적 유의성을 보였으며, Linear response & plateau model에서 최적 질소시비량 ($N_{opt}$)은 138 kg $ha^{-1}$으로 나타났다. 돈분퇴비의 시비반응은 Quadratic model에서 $0.99^{**}$의 유의성 있는 결정계수 ($R^2$)를 보였으며, 최적 퇴비시비량은 각각 9.17 tons $ha^{-1}$으로 나타났다. 상기 결과로 볼 때 사탕무에서 질소와 돈분퇴비의 시비반응을 적절히 평가하기 위해서는 각각 Linear response & plateau model과 Quadratic model을 이용하는 것이 합리적인 것으로 판단되었다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.133-136
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• 2004

This paper proposes a stability condition in affine Takagi-Sugeno (T-S) fuzzy systems with parametric uncertainties and then, introduces the design method of a fuzzy-model-based controller which guarantees the stability. The analysis is based on Lyapunov functions that are continuous and piecewise quadratic. The search for a piecewise quadratic Lyapunov function can be represented in terms of linear matrix inequalities (LMIs).