• 한국산학기술학회논문지
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• 제9권4호
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• pp.871-877
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• 2008

Adaptive 아크 로봇 용접을 위한 용접 공정 변수와 용접 부 형상 사이에 상관관계를 조사하는 것은 중요한 일이다. 하지만 맞대기 용접의 공정에 있어 갭으로 인해 정확한 이면비드를 예측하는 것은 어려운 일이다. 본 연구에서는, 먼저 맞대기 용접을 통해 외부 용접 조건과 용접 비드 형상사이 상관관계가 규명되었고, 이를 응용하여 적절한 이면비드를 얻기 위한 개발이 이루어졌고, 이 연구결과는 산업 전 분야에 폭넓게 사용될 수도 있다. 다중회귀분석법이 공정변수 예측을 위한 연구방법으로 적용되었다. 예측방법의 결과들 또한 비교 및 분석이 이루어졌다.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2006년도 춘계 학술발표회 논문집
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• pp.980-987
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• 2006

Recently, twin-tunnel is often designed considering the aspects of disaster prevention and economic reasons. However, the design cases and the studies are relatively insufficient. By the twin-tunnel excavation, deviate stresses of pillar between tunnels are increased and the increased stresses induce the instability of the twin-tunnel. In this study, numerical analyses about the twin-tunnel behaviour are conducted while varying ground strength, width of pillar and depth of earth cover and a series of regression analyses are carried out by using the results of numerical analyses for the twin-tunnel. Based on the numerical analyses, an estimation method of derived stresses is suggested though the regression analyses. Also, based on the results of regression analyses, an quantitative estimation method considering the reinforcement effects is also suggested. Then various parametric studies are conducted to be considered the reinforcement type and various design parameters. Finally, the efficiency of the suggested method is verified through the results of parametric studies.

• 한국터널지하공간학회 논문집
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• 제13권6호
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• pp.531-555
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• 2011

본 연구에서는 암반대응형 TBM의 소요 사양 산출과 커터헤드 설계를 위한 통계모델을 도출하고자 하였다. 이를 위하여 다양한 암반 조건에서 수집된 871개의 TBM 굴진자료와 51개의 암석 선형절삭시험 결과에 대해 다변량 회귀분석을 실시하여, 다양한 암석 특성과 절삭 조건을 고려한 최적 모델을 도출하였다. 회귀분석을 통해 도출된 설계모델들을 2개의 쉴드터널 현장에 적용한 결과, 커터 관입깊이, 커터 작용력 및 커터 간격과 같은 TBM 핵심 설계항목의 예측결과들이 실제 현장의 굴진결과와 잘 부합되는 것으로 나타났다.

• 한국생활과학회지
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• 제18권6호
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• pp.1267-1276
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• 2009

The purpose of this study is to classify breast types and to inquire about characteristics depending on breast types of women subjects in their twenties. We researched size items affecting breast volume and regression equations for the prediction of breast volume, and thereby, we will be able to provide some basic data, useful to the development of the brassiere depending on breast types. As a result of categorizing the types of three breast types, "type 1" was characterized by big and greatest protrusion of the breast with large breast volume and a large bust, while "type 2" was characterized by flat breasts with the least breast volume and least bust, and "type 3" was characterized by breast location apart from the center front line. Breast volume is significant in establishment of the brassiere cup depending on breast type. Five items such as, the circumference of the breast, the length of the upper breast, the depth of the breast point, the length of the shoulder point-breast point, and the length of the inferior breast were extracted through regression equations for breast volume.

• 한국산학기술학회논문지
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• 제13권1호
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• pp.45-50
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• 2012

본 논문은 CNC 선반에서 Al-6061의 보링 선삭 후 진원도 오차 분석에 관한 것이다. 실험은 실험계획법을 기초로 하여 신호대 잡음비, 분산분석을 사용하여 진원도 오차에 관한 파라미터의 영향을 연구하였다. 그리고 다중선형회귀분석은 진원도 오차의 예측 가능한 수학적 모델을 유도하기 위해 적용되었다. 선삭 파라미터인 고정압, 벽두께, 절삭깊이 그리고 이송속도는 논문의 목적달성을 위해 적용되었고 그 결과를 고찰하였다.

• International Journal of Concrete Structures and Materials
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• 제7권4호
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• pp.303-317
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• 2013

This study evaluates the shear strength of steel fiber reinforced concrete (SFRC) beams from a database, which consists of extensive experimental results of 222 SFRC beams having no stirrups. In order to predict the analytical shear strength of the SFRC beams more precisely, the selected beams were sorted into six different groups based on their ultimate concrete strength (low strength with $f_c^{\prime}$ <50 MPa and high strength with $f_c^{\prime}$ <50 MPa), span-depth ratio (shallow beam with $a/d{\geq}2.5 $and deep beam with a/d<2.5) and steel fiber shape (plain, crimped and hooked). Principal component and multiple regression analyses were performed to determine the most feasible model in predicting the shear strength of SFRC beams. A variety of statistical analyses were conducted, and compared with those of the existing equations in estimating the shear strength of SFRC beams. The results showed that the recommended empirical equations were best suited to assess the shear strength of SFRC beams more accurately as compared to those obtained by the previously developed models.

• Corrosion Science and Technology
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• 제22권1호
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• pp.55-63
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• 2023

The aim of this study was to propose a multiple linear regression (MLR) equation to predict ultimate tensile strength (UTS) of 316L stainless steel with unspecified pit corrosion. Tensile specimens with pit corrosion were prepared using a potentiostatic acceleration test method. Pit corrosion was characterized by measuring ten factors using a confocal laser microscope. Data were collected from 22 tensile tests. At 85% confidence level, total pit volume, maximum pit depth, mean ratio of surface area, and mean area were significant factors showing linear relationships with UTS. The MLR equation using these three significant factors at a 85% confidence level showed considerable prediction performance for UTS. Determination coefficient (R²) was 0.903 with training and test data sets. The yield strength ratio of 316L stainless steel was found to be around 0.85. All specimens with a pit corrosion presented a yield ratio of approximately 0.85 with R² of 0.998. Therefore, pit corrosion did not affect the yield ratio.

• 한국의학물리학회지:의학물리
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• 제1권1호
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• pp.75-84
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• 1990

We have claculated the absorbed dose distributions in water phantom irradiated by high energy photon beam. PDD (Percent Depth Dose) and Beam Profile can be represented by functions of depths and distances by using one dimensional model model based on transport theory. The parameters on scattering and absorption are evaluated by using non-linear regression process method. The values neeessary for calculation are obtained by simple experiment. The calculated values are in good agreement with the measured values.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2005년도 후기학술대회논문집
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• pp.148-149
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• 2005

In this study, among the precision decline main causes of sounding, I suggested the characteristics of sounding data acquired by echo sounder with increasing of turbidity For this, I acquired sounding data by inputting turbidity inducer artificially in artificial water tank. And then achieved regression analysis. Conclusion are as following : Sounding Capabilities can be divided into three ranges according to the turbidity : normal range, critical range and the range where data can not be obtained by an echo sounder

• 한국환경과학회지
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• 제28권8호
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• pp.701-707
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• 2019

Highland farming is agriculture that takes place 400 m above sea level and typically involves both low temperatures and long sunshine hours. Most highland Chinese cabbages are harvested in the Gangwon province. The Ubiquitous Sensor Network (USN) has been deployed to observe Chinese cabbages growth because of the lack of installed weather stations in the highlands. Five representative Chinese cabbage cultivation spots were selected for USN and meteorological data collection between 2015 and 2017. The purpose of this study is to develop a weight prediction model for Chinese cabbages using the meteorological and growth data that were collected one week prior. Both a regression and random forest model were considered for this study, with the regression assumptions being satisfied. The Root Mean Square Error (RMSE) was used to evaluate the predictive performance of the models. The variables influencing the weight of cabbage were the number of cabbage leaves, wind speed, precipitation and soil electrical conductivity in the regression model. In the random forest model, cabbage width, the number of cabbage leaves, soil temperature, precipitation, temperature, soil moisture at a depth of 30 cm, cabbage leaf width, soil electrical conductivity, humidity, and cabbage leaf length were screened. The RMSE of the random forest model was 265.478, a value that was relatively lower than that of the regression model (404.493); this is because the random forest model could explain nonlinearity.