• 제어로봇시스템학회논문지
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• 제9권3호
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• pp.210-217
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• 2003

We introduced a scheme for finding an optimal data association matrix that represents the relationships between the measurements and tracks in multi-target tracking (MIT). We considered the relationships between targets and measurements as Markov Random Field and assumed a priori of the associations as a Gibbs distribution. Based on these assumptions, it was possible to reduce the MAP estimate of the association matrix to the energy minimization problem. After then, we defined an energy function over the measurement space that may incorporate most of the important natural constraints. To find the minimizer of the energy function, we derived a new equation in closed form. By introducing Lagrange multiplier, we derived a compact equation for parameters updating. In this manner, a pair of equations that consist of tracking and parameters updating can track the targets adaptively in a very variable environments. For measurements and targets, this algorithm needs only multiplications for each radar scan. Through the experiments, we analyzed and compared this algorithm with other representative algorithm. The result shows that the proposed method is stable, robust, fast enough for real time computation, as well as more accurate than other method.

• 여성건강간호학회지
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• 제17권4호
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• pp.328-336
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• 2011

Purpose: The purpose of this study is to develop the optimal nursing fee for nurse-midwifery center (MC) in the national health insurance system. Methods: The three methodologies used to calculate the conversion factors for the MCs in the national health insurance include cost accounting method, sustainable growth rate (SGR) model, and index model. In this study, the macro-economic indicators and the national statistics were used to estimate the conversion factors for the MCs. Results: The optimal nursing fee for the MCs in 2011 was estimated to be an increase of 57.7% by cost accounting analysis, a decrease of 17.1% by SGR model, and a decrease of 16.1% by index model. The results from SGR model and index model could had been biased due to the upswing of medical spendings in the short-term period (2008~2009). A sensitivity analysis of pre-delivery subsidy program for OB & GYN hospitals and clinics showed that the program has substantially diminished the demand for the MC services. Conclusion: More reliable methodologies to estimate nursing fees precisely are required to prove the value of nurses' services and a government subsidy program for the MC services should be followed from a social perspective.

• 한국농공학회논문집
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• 제50권6호
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• pp.27-35
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• 2008

This study aims to estimate the optimal probability distribution of daily electricity generation by wind power, in order to contribute in rural green-village planning. Wind power generation is now being recognized as one of the most popular sources for renewable resources over the country. Although it is also being adapted to rural area for may reasons, it is important to estimate the magnitudes of power outputs with reliable statistical methodologies while applying historical daily wind data, for correct feasibility analysis. In this study, one of the well-known statistical methodology is employed to define the appropriate statistical distributions for monthly power outputs for specific rural areas. The results imply that the assumption of normal distributions for many cases may lead to incorrect decision-making and therefore lead to the unreliable feasibility analysis. Subjective methodology for testing goodness of fit for normal distributions on all the cases in this study, provides possibilities to consider the other various types of statistical distributions for more precise feasibility analysis.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(I)
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• pp.311-315
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• 1987

In this paper an efficient algorithm to estimate the volume and surface area and the reconstruction algorithm for 3-dimensional graphics are presented. The graph theory is used to estimate the optimal quantitative factors. To improve the computing efficiency, the algorithm to get proper contour points is performed by applying several tolerances. The search and the given arc cost is limited according to the change of curvature of the cross-sectional contour. For mathematical model, these algorithms for volume estimation based on polyhedral approximation are applied to the selected optimal surface. The results show that the values of the volume and surface area for tolerances 1.0005, 1.001 and 1.002 approximate to values for tolerances 1.000 resulting in small errors. The reconstructed three-dimensional images are sparse and consist of larger triangular tiles between two cross sections as tolerance is increasing.

• 기술혁신학회지
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• 제10권2호
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• pp.183-205
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• 2007

본 연구는 기술력평가에 근거해서 중소기업 부실예측 가능성을 사전에 예측할 수 있는 최적 판별 모형을 개발 제안하였다. 판별모형에 포함될 설명변수는 요인분석과 판별모형의 단계별 선택방법에 의하여 선정되었다. 분석결과 선형판별모형이 로지스틱판별모형보다 임계확률 관점에서 적절한 것으로 나타났다. 최적 선형판별모형의 분류 정분류율은 70.4%, 분류 예측력은 67.5%로 나타났다. 최적 선형판별모형의 활용도를 높이기 위해서 확실 범주와 유보범주를 구분할 수 있는 경계값을 설정하였다. 분석결과를 활용하면 기술금융 취급기관은 부실위험 평가와 더불어 기술금융 신청기업의 순위를 부여할 때 유용하게 사용할 수 있을 것으로 기대된다.

• 한국농공학회지
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• 제22권3호
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• 대한기계학회논문집A
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• 제30권4호
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• pp.465-472
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• 2006

Recently, the regulations of the government and the concerns of people have rise to the interest in noise pollution levels as compared to other vehicles. In this area, many researchers have studied to reduce this noise in the field of automotive engineering. This paper proposes an optimal design scheme to reduce the noise of the intake system by adapting Kriging with two meta-heuristic techniques. For this, as a measuring tool for the performance of the intake system, the performance prediction software, was used. Then, the length and radius of each component of the current intake system are selected as input variables and the orthogonal arrays is adapted as a space-filling design. With these simulated data, we can estimate a correlation parameter in Kriging by solving the nonlinear problem with a genetic algorithm and find an optimal level for the intake system by optimizing Kriging estimated with simulated annealing. We notice that this optimal design scheme gives noticeable results and is a preferable way to analyze the intake system. Therefore, an optimal design for the intake system is proposed by reducing the noise of its system.

• 한국소음진동공학회논문집
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• 제19권5호
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• pp.509-515
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• 2009

This paper proposes an optimal design scheme to reduce the noise of the engine cooling fan by adapting Kriging with two meta-heuristic techniques. An engineering model has been developed for the prediction of the noise spectrum of the engine cooling fan. The noise of the fan is expressed as the discrete frequency noise peaks at the BPF and its harmonics and line spectrum at the broad band by noise generation mechanisms. The object of this paper is to find the optimal design for noise reduction of the engine cooling fan. We firstly show a comparison of the measured and calculated noise spectra of the fan for the validation of the noise prediction program. Orthogonal array is applied as design of experiments because it is suitable for Kriging. With these simulated data, we can estimate a correlation parameter of Kriging by solving the nonlinear problem with genetic algorithm and find an optimal level for the noise reduction of the cooling fan by optimizing Kriging estimates with simulated annealing. We notice that this optimal design scheme gives noticeable results. Therefore, an optimal design for the cooling fan is proposed by reducing the noise of its system.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2007년도 추계학술대회논문집
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• pp.1307-1312
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• 2007

This paper proposes an optimal design scheme to reduce the noise of the engine cooling fan by adapting Kriging with two meta-heuristic techniques. An engineering model has been developed for the prediction of the noise spectrum of the engine cooling fan. The noise of the fan is expressed as the discrete frequency noise peaks at the BPF and its harmonics and line spectrum at the broad band by noise generation mechanisms. The object of this paper is to find the Optimal Design for Noise Reduction of the Engine Cooling Fan. We firstly show a comparison of the measured and calculated noise spectra of the fan for the validation of the noise prediction program. Orthogonal array is applied as design of experiments because it is suitable for Kriging. With these simulated data, we can estimate a correlation parameter of Kriging by solving the nonlinear problem with genetic algorithm and find an optimal level for the noise reduction of the cooling fan by optimizing Kriging estimates with simulated annealing. We notice that this optimal design scheme gives noticeable results. Therefore, an optimal design for the cooling fan is proposed by reducing the noise of its system.

• 한국수자원학회논문집
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• 제38권1호
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• pp.25-35
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• 2005

요즘 다목적댐의 수력발전을 일으킬 수 있는 수자원은 용수공급이 증가함에 따라서 점점 감소하고 있는 형편이다. 한편 국내 수력 발전량의 거래가 다자간의 시장경제 체제로 형성될 경우, 수력에너지 생산자는 최적 공급량과 공급의 수문학적 신뢰도 수준을 제시해야 한다. 이에 본 연구에서는 금강 수계 내 위치한 용담다목적댐의 수력 발전소에서 공급가능한 발전량과 공급 신뢰도를 평가하기 위하여 저수지 조작 기법으로 선형계획법을 적용하였고 1차원 조사법을 이용하여 유입량의 신뢰도와 수력 발전 공급량의 최적치를 결정하였고 그 주요 결과를 제시하였다.