• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.13 no.4
• /
• pp.75-81
• /
• 1999

This paper presents in the rrethod power demand estimated of consuming facility algorithm using orthogonal polynomial regression rmdel. Estimation rmdel presented can use mathematical rrethod consists. of extrapolation and correlation rrethod, Computation tirre and capacity of presented rmdel was rmre economic than multiple regression rrodel because low-order equation can use in the high-order equation without sorre correction, and vice-versa. Therefore this rmthed can be very usefulness rmthed in the power demand estimation Fourth-order rrodel was very good armng this rrodel that was coJTJp)Sed the estimation rmdel of second, third and fourth-order. Power demand estimated result of consuming facility using correlation rrethod was good in the percentage error of about 2[%1 Also It was to verify efficiency and awroPJiation the estimated rmdel that estimation percentage error was about 1[%] in the oower demand estimated result of 1997.

• Korean journal of applied entomology
• /
• v.26 no.1 s.70
• /
• pp.31-36
• /
• 1987

A piecewise linear regression model able to describe disease progress curves with simplicity and flexibility was developed in this study. The model divides whole epidemic into several pieces of simple linear regression based on changes in pattern of disease progress in the epidemic and then incorporates the pieces of linear regression into a single mathematical function using indicator variables. When twelve epidemic data obtained from the field experiments were fitted to the piecewise linear regression model, logistic model and Gompertz model to compare statistical fit, goodness of fit was greatly improved with piecewise linear regression compared to other two models. Simplicity, flexibility, accuracy and ease in parameter estimation of the piece-wise linear regression model were described with examples of real epidemic data. The result in this study suggests that piecewise linear regression model is an useful technique for modeling plant disease epidemic.

• Journal of Convergence for Information Technology
• /
• v.9 no.6
• /
• pp.1-6
• /
• 2019

In this study, the development of a weight estimation model of electronic scale with nonlinear characteristics is presented using polynomial regression analysis. The output voltage of the load cell was measured directly using the reference mass. And a polynomial regression model was obtained using the matrix and curve fitting function of MS Office Excel. The weight was measured in 100g units using a load cell electronic scale measuring up to 5kg and the polynomial regression model was obtained. The error was calculated for simple($1^{st}$), $2^{nd}$ and $3^{rd}$ order polynomial regression. To analyze the suitability of the regression function for each model, the coefficient of determination was presented to indicate the correlation between the estimated mass and the measured data. Using the third order polynomial model proposed here, a very accurate model was obtained with a standard deviation of 10g and the determinant coefficient of 1.0. Based on the theory of multi regression model presented here, it can be used in various statistical researches such as weather forecast, new drug development and economic indicators analysis using logistic regression analysis, which has been widely used in artificial intelligence fields.

• 한국IT서비스학회:학술대회논문집
• /
• 2003.05a
• /
• pp.145-152
• /
• 2003

본 연구의 선행 연구에서는 증권시스템의 기능점수를 직접 구하여 기능점수와 운영비용과의 회귀분석을 실시하였다. 수집된 자료의 건수가 적었던 관계로 통계적 유의성을 충분하게 확보하지 못하였다. 따라서 본 연구에서는 증권시스템의 기능점수를 직접 측정하는 것이 현실적으로 많은 제약이 있음을 감안하여, 비교적 자료 수집이 용이한 프로그램 본 수를 측정하였다. 이러한 프로그램 본 수는 스텝 수로 1차 변환이 되었고, 스텝 수는 다시 기능점수로 2차 변환이 되었다. 이렇게 변환된 기능점수와 운영비용과의 회귀분석을 실시하였으며, 증권정보시스템 운영비용 추정 모델을 제시하였다.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.39 no.4
• /
• pp.314-320
• /
• 2011

In this work, optimization of two-stage shock absorption system for lunar lander has been carried out. Because of complexity of impact phenomena of shock absorption system, a 1-D constitutive model is proposed to describe the behavior of shock absorption system. Quadratic polynomial regression meta-model is constructed by using a commercial software ABAQUS with the proposed 1-D constitutive model, and sequential approximate optimization of two-stage shock absorption system has been carried out along with the constructed meta-model. Through the optimization, it is verified that landing impact force on lunar lander can be considerably reduced by changing the cell size and foil thickness of honeycomb structure in two-stage shock absorption system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2004.10a
• /
• pp.429-432
• /
• 2004

본 논문은 기존의 퍼지 다항식 뉴럴 네트워크 (Fuzzy Polynomial Neural Networks ; FPNN) 모델을 이용하여 비선형성 데이터에 대한 추론을 제안한다. 복잡한 비선형 시스템의 모델동정을 위하여 생성된 GMDH 방법에 기초한 FPNN의 각 노드는 퍼지 규칙을 기반으로 구축되었으며, 층이 진행되는 동안 모델 스스로 노드의 선택과 제거를 통해 최적의 네트워크 구조를 생성할 수 있는 유연성을 가지고 있다. FPNN 각각의 활성노드를 퍼지다항식 뉴론(Fuzzy Polynomial Neuron ; FPN)이라고 표현한다. FPNN의 후반부 구조는 입출력 변수 사이 의 간략과 회귀다항식 (1차, 2차, 변형된 2차식) 함수에 의해 구현된다. 규칙의 전반부 멤버쉽 함수는 삼각형과 가우시안형의 멤버쉽 함수가 사용된다. 또한 유전자 알고리즘을 사용하여 각노드의 부분표현식을 구성하는 입력변수의 수, 입력변수와 차수의 선택 동조를 통하여 최적의 Genetic Algorithms(GAs)을 이용한 FPNN모델을 설계하는 것이 유용하고 효과적임을 보인다.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.46 no.1
• /
• pp.14-22
• /
• 2009

By calculating the differences between two images, which are captured with the same scene at different time, we can detect a set of outliers, such as occluding objects due to moving vehicles. To reduce the influence from the different intensity properties of the images, a simple technique that reruns the regression, which is based on the polynomial regression model, is employed. For a robust detection of outliers, the image difference is normalized by the noise variance. Hence, an accurate estimate of the noise variance is very important. In this paper, using an empirically obtained correction constant is proposed. Numerical analysis using both synthetic and real images are also shown in this paper to show the robust performance of the detection algorithm.

• Journal of Service Research and Studies
• /
• v.14 no.1
• /
• pp.27-43
• /
• 2024

The market share of online platform services in the used car market continues to expand. And The used car online platform service provides service users with specifications of vehicles, accident history, inspection details, detailed options, and prices of used cars. SUV vehicle type's share in the domestic automobile market will be more than 50% in 2023, Sales of Hybrid vehicle type are doubled compared to last year. And these vehicle types are also gaining popularity in the used car market. Prior research has proposed a used car price prediction model by executing a Machine Learning model for all vehicles or vehicles by brand. On the other hand, the popularity of SUV and Hybrid vehicles in the domestic market continues to rise, but It was difficult to find a study that proposed a used car price prediction model for these vehicle type. This study selects a used car price prediction model by vehicle type using vehicle specifications and options for Sedans, SUV, and Hybrid vehicles produced by domestic brands. Accordingly, after selecting feature through the Lasso regression model, which is a feature selection, the ensemble model was sequentially executed with the same sampling, and the best model by vehicle type was selected. As a result, the best model for all models was selected as the CBR model, and the contribution and direction of the features were confirmed by visualizing Tree SHAP Value for the best model for each model. The implications of this study are expected to propose a used car price prediction model by vehicle type to sales officials using online platform services, confirm the attribution and direction of features, and help solve problems caused by asymmetry fo information between them.

• Journal of Energy Engineering
• /
• v.4 no.1
• /
• pp.103-114
• /
• 1995

본 연구는 원자력발전소용 시뮬레이션 언어인 DSNP(Dynamic Simulator for Nuclear Power-plants)언어를 이용하여 CANDU-6 발전소 운전 모사 프로그램을 구성함으로써 핵심계통인 1차 냉각재 계통(PHTS)과 2차 계통 일부가 정상 및 과도조건에서 보일 수 있는 운전 상태를 연구하였다. DSNP 프로그램은 원자로심과 증기발생기에서의 열전달 모델, 열수송계통 펌프 모델 및 가압기 열수력 모델을 포함하고 있으며, 파이프(pipe)라는 단위 구성체를 이용하여 1차 냉각재계통을 노드화하여 계통 모사가 실현된다. 정상상태 100% 전출력 운전시 대표적인 운전변수를 기준으로 DSNP 결과와 CANDU-6 발전소 설계치를 비교해 본 결과 서로 매우 근사한 값을 나타내었으며, 이는 과도상태 모사의 초기조건으로 합당한 것으로 판단된다. 본 연구에서 선택된 과도상태 모사시 DSNP 프로그램은 매우 안정된 최종정상상태를 얻음에 따라 원자로의 기계 물리학적 변화를 합리적으로 모사하고 있음을 알 수 있었다. 최종 정상상태 회귀 이전의 동적 거동을 원자로 설계자료인 예비 안전성 평가 보고서(PSAR)와 비교한 결과 단기적 거동은 PSAR 결과와 다소 다른 점이 있었으나 전체적으로 합리적인 운전변수 값을 얻을 수 있었다. 단기적 거동에 대한 입증은 원자로 운전 자료를 통하여 가능할 것으로 사료된다. 이상과 같이 본 연구를 통해 구성한 DSNP 프로그램은 보완 및 개선의 여지가 있으나 현재의 수준으로도 CANDU-6 발전소의 일부 과도상태 모사가 가능한 것으로 판단된다.

• Journal of Korean Society of Transportation
• /
• v.23 no.1
• /
• pp.33-44
• /
• 2005

Railroad crossing crashes are fewer than road crashes, but with regard to crash severity, they can be serious injury crashes. There should be, therefore, enormous efforts to increase the safety of railroad crossings. The objective of this paper is to identify and understand factors associated with railroad crossing crashes. Statistical models are used to examine the relationships between crossing accidents and geometric elements of crossings. The results show the Poisson model is the most appropriate method for the crossing accidents, because overdispersion was not observed. This study identifies seven significant factors associated with railroad crossing crashes through the main and variant models. With regard to explanatory factors on crossing safety, the total traffic volume, daily train volume, presence of commercial area around crossings, distance of train detector from crossings, time duration between the activation of warning signals and gates, crossing types, and speed hump were found to affect the safety of railroad crossings.