• The Journal of the Korea Contents Association
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• v.15 no.1
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• pp.475-481
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• 2015

We use polynomial regression instead of linear regression if there is a nonlinear relation between a dependent variable and independent variables in a regression analysis. The performance of polynomial regression, however, may deteriorate because of the correlation caused by the power terms of independent variables. We present a polynomial regression model for the numerical inversion of PGF and show that polynomial regression results in the deterioration of the estimation of the coefficients. We apply principal components regression to the polynomial regression model and show that principal components regression dramatically improves the performance of the parameter estimation.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.189-193
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• 2006

대체용수원의 개발이 시급하게 대두되어지고 있는 가운데 제한된 수자원을 보다 효과적으로 사용하기 위한 하나의 방법으로 지하댐(Groundwater Dam) 건설을 이용한 지하수 자원의 개발이 하나의 방법으로 제안되었다. 하지만 해안지역에 설치된 지하댐을 운영할 경우 지하수위 변동에 따른 염수의 침입을 고려하여 운영하여야 한다. 특히 갈수시는 지하수위 하강이 강하게 나타나는 시기로 지하수위는 지하댐 최적운영을 위한 중요한 지표가 된다. 특히 강우량 자료를 활용한 가뭄지수와 지하수위의 관계를 설명 할 수 있다면 예상 강우자료를 활용한 장래의 지하수위를 예측 할 수 있으며 이것은 지하댐 운영에 매우 효과적으로 활용 할 수 있을 것이다. 본 연구에서는 기존의 강우와 예상 강우 자료를 활용하여 지하수위 예측기법을 개발하였다. 과거 강수량의 일이동 평균값을 바탕으로 한 다항 회귀모델을 수립하여, 계절적 특성을 고려한 구간을 분리하여 적용하였다. 예측된 지하수위의 정확성을 알아보기 위해 관측된 지하수위와 예측된 지하수위를 비교 분석하였다. 분석 결과 단순회귀기법을 지하수위를 예측한 경우 $0.62{\sim}0.63$의 상관계수를 보인반면 다항회귀기법을 적용한 결과 $0.62{\sim}0.84$로 상관계수가 증가하였다. 대체적으로 관측된 지하수위와 예측된 지하수위는 비슷한 경향을 보였다. 따라서 지하댐 운영에 있어 최적의 취수량을 개발하기위해 일강우자료를 활용한 지하수위 예측기법의 활용성은 매우 높은 것으로 판단된다.

• Journal of Korean Society of Transportation
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• v.27 no.2
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• pp.47-56
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• 2009

Effective detection and correction of outliers of raw traffic data collected from the field is of keen interest because reliable traffic information is highly dependent on the quality of raw data. Global positioning system (GPS) based traffic surveillance systems are capable of producing individual vehicle speeds that are invaluable for various traffic management and information strategies. This study proposed a locally weighted regression (LWR) based filtering method for individual vehicle speed data. An important feature of this study was to propose a technique to generate synthetic outliers for more systematic evaluation of the proposed method. It was identified by performance evaluations that the proposed LWR-based method outperformed an exponential smoothing. The proposed method is expected to be effectively utilized for filtering out raw individual vehicle speed data.

• Korea journal of population studies
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• v.30 no.1
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• pp.49-66
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• 2007

본 연구는 2001년 한국에서 사망한 60세 이상 노인들 62,000명의 사망기록 자료를 이용하여 사망원인의 다양성을 보여주는 한편 치매에 의한 사망원인을 가장 잘 예측할 수 있는 변수를 경험적으로 규명하고자 실시하였다. 이와 같은 목적을 위한 연구내용은 다음과 같다. 첫째, 노인들의 주요 사망원인에 해당하는 악성종양, 뇌혈관 질환, 심장병, 당뇨, 만성 호흡기 질환, 치매, 고혈압, 간 질환, 사고, 결핵 및 기타 질병 등 11개 사망원인에 대하여 빈도분석을 실시하였다. 둘째, 60세 이상 사망자들 가운데 치매에 의한 사망원인과 나머지 19개의 사망원인을 비교하여 치매에 의한 사망에 영향을 미치는 요인들을 다항로지스틱회귀분석을 통해 분석하였다. 그 결과, 한국의 노인인구 가운데 연령이 높을수록 치매로 인하여 사망할 가능성(우도비)이 높으며 여성이 남성에 비해 치매에 의하여 사망할 가능성이 높은 것으로 밝혀졌다. 그러나 교육수준이 높을수록 치매에 의하여 사망할 가능성이 낮은 것으로 나타났으며 거주지역은 치매에 의한 사망과 통계적으로 유의미한 관계가 있었으나 일관성은 없는 것으로 밝혀졌다. 한편 결혼지위는 치매에 의한 사망과 통계적으로 유의미한 관계가 없는 것으로 나타났다.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.589-602
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• 2008

This article studies on disability pensioners' characteristic with multinomial logit and logistic regression model. Seven factors are examined on whether each factor is reflected in degree of disability in the disability pension. By incorporating multinomial logit and logistic regression model, effectiveness and characteristic of the seven factors are investigated on the degree of disability. Result shows all the seven factors are significant on the degree of disability, while among the seven, five factors, age, sex, type of coverage, type of category, insured duration show a trend in degree of disability and the other two, cause of disability and class of standard monthly income are not effective on trend in degree of disability. Results from analyses might be useful for disability pension management.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.2
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• pp.98-103
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• 2002

In case of power demand forecasting, the most important problems are to deal with the load of special-days. Accordingly, this paper presents the method that forecasting long (the Lunar New Year, the Full Moon Festival) and short(the Planting Trees Day, the Memorial Day, etc) special-days peak load using neural networks and regression models. long and short special-days peak load forecast by neural networks models uses pattern conversion ratio and four-order orthogonal polynomials regression models. There are using that special-days peak load data during ten years(1985∼1994). In the result of special-days peak load forecasting, forecasting % error shows good results as about 1 ∼2[%] both neural networks models and four-order orthogonal polynomials regression models. Besides, from the result of analysis of adjusted coefficient of determination and F-test, the significance of the are convinced four-order orthogonal polynomials regression models. When the neural networks models are compared with the four-order orthogonal polynomials regression models at a view of the results of special-days peak load forecasting, the neural networks models which uses pattern conversion ratio are more effective on forecasting long special-days peak load. On the other hand, in case of forecasting short special-days peak load, both are valid.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.177-179
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• 2023

본 연구에서는 사회복지시설 종사사의 직무만족도 유형을 살펴보고 유형별 예측변인과의 영향관계를 검증하였다. 이러한 연구목적을 검증하기 위해 보건복지부의 '사회복지시설 실태조사'(2014년) 데이터에서 직무만족도 변인에 모두 응답한 11,660명을 최종 분석하였다. 잠재프로파일 분석결과, 사회복지사의 직무만족도 유형은 4집단으로 나타나 '최상 직무만족도집단', '중상 직무만족도집단', '중간 직무만족도집단', '최하 직무만족도집단'으로 명명하였다. 다항로지스틱 분석결과, CLASS4(최상 직무만족도집단)를 준거집단으로 하여 CLASS1(최하 직무만족도집단)과 비교해 노동강도대비 보수수준 평가, 타직종대비 보수수준 평가, 시설안전도, 인권보장도를 높게 인식할수록 CLASS4(최상 직무만족도집단)에 속할 확률이 높아지는 것으로 나타났다. 다만, 이직의사는 낮을수록 CLASS4(최상 직무만족도집단)에 속할 확률이 높아지는 것으로 나타났다. CLASS4를 준거집단으로 하여 CLASS2집단, CLASS3집단도 비교분석 하였다.

• Journal of the Korean Association of Geographic Information Studies
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• v.24 no.4
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• pp.148-163
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• 2021

The diversification of the New Deal urban regeneration projects, that started in 2017 in accordance with the "Special Act on Urban Regeneration Activation and Support", generated the increased demand for the accuracy of data-driven diagnosis and project type forecast. Thus, this research was conducted to develop an application model able to identify the most appropriate New Deal project type for "eup", "myeon" and "dong" across the country. Data for application model development were collected through Statistical geographic information service(SGIS) and the 'Urban Regeneration Comprehensive Information Open System' of the Urban Regeneration Information System, and data for the analysis model was constructed through data pre-processing. Four models were derived and simulations were performed through polynomial regression analysis and multinomial logistic regression analysis for the application of the appropriate New Deal project type. I verified the applicability and validity of the four models by the comparative analysis of spatial distribution of the previously selected New Deal projects by targeting the sites located in Seoul by each model and the result showed that the DI-54 model had the highest concordance rate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.2
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• pp.511-516
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• 2013

The thickness and deflection of melting parts of the glass edge reach the biggest effect on the intensity and thermal insulation performance. During the sealing process using a hydrogen mixed gas torch, the thickness and the deflection effect of the edge part are affected by process parameters. In order to analyze the correlative relationship of the thickness prediction and the deflection of the edge part according to the process parameters, data was obtained by conducting sealing experiments. The main effects and interaction effects of process parameters for the thickness and the shape of the glass edge parts were analyzed through the design of experiment. A mathematical experiment equation that can predict the thickness and deflection of the edge part according to the process parameters was developed by conducting multiple regression equations.

• The Journal of Engineering Geology
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• v.31 no.1
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• pp.31-42
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• 2021

Database of Cut-slope management system (CSMS) has been constructed based on investigations of all slopes on the roads of the whole country. The investigation data is documented by human, so it is inevitable to avoid human-error such as missing-data and incorrect entering data into computer. The goal of this paper is constructing a prediction model based on several machine-learning algorithms to solve those imperfection problems of the CSMS data. First of all, the character-type data in CSMS data must be transformed to numeric data. After then, two algorithms, i.g., multinomial logistic regression and deep-neural-network (DNN), are performed, and those prediction models from two algorithms are compared. Finally, it is identified that the accuracy of DNN-model is better than logistic model, and the DNN-model will be utilized to improve data-quality.