• 제목/요약/키워드: Regression Analysis Method

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Development of a Probability Prediction Model for Tropical Cyclone Genesis in the Northwestern Pacific using the Logistic Regression Method

  • Choi, Ki-Seon;Kang, Ki-Ryong;Kim, Do-Woo;Kim, Tae-Ryong
    • 한국지구과학회지
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    • 제31권5호
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    • pp.454-464
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    • 2010
  • A probability prediction model for tropical cyclone (TC) genesis in the Northwestern Pacific area was developed using the logistic regression method. Total five predictors were used in this model: the lower-level relative vorticity, vertical wind shear, mid-level relative humidity, upper-level equivalent potential temperature, and sea surface temperature (SST). The values for four predictors except for SST were obtained from difference of spatial-averaged value between May and January, and the time average of Ni$\tilde{n}$o-3.4 index from February to April was used to see the SST effect. As a result of prediction for the TC genesis frequency from June to December during 1951 to 2007, the model was capable of predicting that 21 (22) years had higher (lower) frequency than the normal year. The analysis of real data indicated that the number of year with the higher (lower) frequency of TC genesis was 28 (29). The overall predictability was about 75%, and the model reliability was also verified statistically through the cross validation analysis method.

제진재의 최적배치를 이용한 차량공조시스템의 음질개선 (Improvement of Sound Quality for the Vehicle HVAC System Using Optimum Layout of Damping Material)

  • 오재응;황동건;박상길;윤태건;심현진;이정윤
    • 대한기계학회논문집A
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    • 제30권6호
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    • pp.728-733
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    • 2006
  • The reduction of the Vehicle interior noise has been the main interest of NVH engineers. The driver's perception on the vehicle noise is affected largely by psychoacoustic characteristic of the noise as well as the SPL. In particular, the HVAC sound among the vehicle interior noise has been reflected sensitively in the side of psychology. In previous study, we have developed to verify identification of source for the vehicle HVAC system through multiple-dimensional spectral analysis. Also we carried out objective assessments on the vehicle HVAC noises and subjective assessments have been already performed with 30 subjects. In this study, the linear regression models were obtained for the subjective evaluation and the sound quality metrics. The regression procedure also allows you to produce diagnostic statistics to evaluate the regression estimates including appropriation and accuracy. Appropriation of regression model is necessary to $R^2$ value and F-value. And testing for regression model is necessary to independence, homoscedesticity and normality. Also we selected optimum layout of damping material using Taguchi method. As a result of application, sound quality is improved more quietly, powerfully, even though costly, and smoothly.

회귀분석법에 의한 임플란트 경부골 응력의 정량적 분석에 대한 연구 (Investigation of the Regression Analysis Method for a Quantitative Evaluation of Implant Crestal Bone Stresses)

  • 김우식;조광헌;이규복
    • 구강회복응용과학지
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    • 제24권3호
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    • pp.299-310
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    • 2008
  • 경부골 최대응력을 안정적으로 산출하기 위해서, 경부 디자인 형상이 비교적 단순한 메가젠 임플란트 모델을 대상으로, 유한요소 모델링을 통하여 경부골의 응력분포를 계산하였다. 그리고 산출된 응력분포를 회귀분석법으로 통계 처리하여 응력 집중점의 응력을 정량화 하였다. 결과는 모든 모델에서 경부골 응력은 치밀골 외면에 집중되었으며, 그 범위는 0.5mm 이내였다. 회귀분석법을 활용하기 위해서는 mesh 정밀도가 높아야 했으며, 이 경우 특이점의 최대 응력을 안정적으로 산출 할 수 있었다.

하천홍수량의 지역화 회귀모형개발을 위한 지역빈도해석 (Regional Frequency Analysis for a Development of Regionalized Regression Model of River Floods)

  • 노재식;이길춘
    • 대한토목학회논문집
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    • 제13권3호
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    • pp.139-154
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    • 1993
  • 본 연구는 자연하천 유역에서의 수위관측점들을 대상으로 지점 홍수빈도해석을 실시하고 하천홍수량의 지역빈도해석에 의한 지역화 회귀모형을 개발한 것이다. 홍수빈도해석은 국내 주요 5대 하천유역인 한강, 금강, 영산강, 섬진강 및 낙동강 유역내에 있는 자연하천관측점들을 대상으로 홍수빈도모형을 이용하여 지점별 홍수량의 크기 및 빈도를 추정하였으며, 이를 바탕으로 홍수빈도예측을 위한 모형의 적용성과 효용성을 비교, 검토하였다. 그 결과 단기간 기록년수의 자료에서는 부분기간치계열 방법의 POT(Peaks Over a Threshold)모형이 연최대치계열 방법의 ANNMAX(ANNual MAXimum) 모형보다 효과적이고 합리적임이 판명되었다. 지역 홍수빈도해석에서 홍수빈도모형에 의한 지점별 홍수추정량과 홍수유출에 영향을 미치는 지형학적 유역 특성인자들간의 상관분석법에 의해 미계측 지점에서의 설계홍수량 추정이 용이한 지역화 회귀모형을 개발하고, 첨두홍수량과 유역 특성인자들간의 상관도를 재현기간별로 작성 제시하였다.

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건설자재 미세먼지 제거율 평가를 위한 선형 회귀 분석법 제안 (Linear Regression Analysis to Evaluate the Particulate Matter Removal Rate of Functional Construction Materials)

  • 박광민;민경성;정상화;노영숙
    • 한국구조물진단유지관리공학회 논문집
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    • 제25권5호
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    • pp.86-93
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    • 2021
  • 미세먼지를 제거하기 위하여 미세먼지 제거 기능성 건설자재가 개발되고 있다. 그러나 미세먼지 제거율 평가 방법 및 기반 시설은 국내에 전무한 실정이다. 따라서 본 연구에서는 입자상 미세먼지 제거 성능을 평가하기 위해 미세먼지 제거율 시험 챔버를 구축하고 입자상 미세먼지 제거율 평가 방법을 제시하는 것을 목적으로 하였다. 결과적으로 건설자재는 미세먼지가 발생하는 환경에서 유효성을 가지기 때문에, 시험 입자 주입 단계 구간를 비교 대상으로 제안하였다. 미세먼지 주입 단계에서 측정한 모든 질량농도값에서 선형 회귀 분석으로 얻어진 기울기값을 상대 비교함으로써 미세먼지 제거율 평가를 제안하였다. 본 방법은 모든 측정값을 대상으로 하고 측정값 변동성에 대한 평가를 결정계수(R2)로 평가할 수 있어서 미세먼지 제거율 결과값의 신뢰성을 확보할 수 있다.

중도절단된 자료에 대한 가법회귀모형 (Additive Regression Models for Censored Data)

  • 김철기
    • 품질경영학회지
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    • 제24권1호
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    • pp.32-43
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    • 1996
  • In this paper we develop nonparametric methods for regression analysis when the response variable is subject to censoring that arises naturally in quality engineering. This development is based on a general missing information principle that enables us to apply, via an iterative scheme, nonparametric regression techniques for complete data to iteratively reconstructed data from a given sample with censored observations. In particular, additive regression models are extended to right-censored data. This nonparametric regression method is applied to a simulated data set and the estimated smooth functions provide insights into the relationship between failure time and explanatory variables in the data.

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Analysis of Characteristics of All Solid-State Batteries Using Linear Regression Models

  • Kyo-Chan Lee;Sang-Hyun Lee
    • International journal of advanced smart convergence
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    • 제13권1호
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    • pp.206-211
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    • 2024
  • This study used a total of 205,565 datasets of 'voltage', 'current', '℃', and 'time(s)' to systematically analyze the properties and performance of solid electrolytes. As a method for characterizing solid electrolytes, a linear regression model, one of the machine learning models, is used to visualize the relationship between 'voltage' and 'current' and calculate the regression coefficient, mean squared error (MSE), and coefficient of determination (R^2). The regression coefficient between 'Voltage' and 'Current' in the results of the linear regression model is about 1.89, indicating that 'Voltage' has a positive effect on 'Current', and it is expected that the current will increase by about 1.89 times as the voltage increases. MSE found that the mean squared error between the model's predicted and actual values was about 0.3, with smaller values closer to the model's predictions to the actual values. The coefficient of determination (R^2) is about 0.25, which can be interpreted as explaining 25% of the data.

VoIP 망에서의 프레임손실은닉을 위한 비선형 회귀분석 기법 (A Nonlinear Regression Analysis Method for Frame Erasure Concealment in VoIP Networks)

  • 최승호;성호상
    • 한국인터넷방송통신학회논문지
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    • 제9권5호
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    • pp.129-132
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    • 2009
  • 프레임 손실은 VoIP 망에서의 음질 저하의 주요 원인이다. 본 논문에서는 VoIP 망에서 주로 사용되는 CELP 기반 음성부호화기의 음질 저하를 최소화하기 위해 비선형 회귀분석 기반의 프레임손실은닉 알고리즘을 제안한다. 제안된 기법은 ITU-T G.729 표준 코덱에 적용되었으며, 기존 방법들에 비해 향상된 PESQ 성능을 보였다.

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반응표면분석에 의한 쌀 압출성형물의 품질평가 (Quality Measurement of Rice - Mixture Extrudate by the Response Surface Regression Analysis)

  • 고광진;김준평
    • 동아시아식생활학회지
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    • 제1권3호
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    • pp.305-311
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    • 1991
  • The study was designed to investigate overall acceptability of rice extrudate with added ginseng flour extruded by single screw extruder. Graphic three dimension analysis on response surface regression was conducted for overall acceptability evaluated by balanced incomplete block design. Overall acceptability, which formed a saddle point, increased as moisture content increased at lower die temperature, and as moisture content decreased at higher die temperature. Critical values of each variable which indicated optimum response are 5.0% ginseng content, 17.8% moisture content and 104.6$^{\circ}C$ die temperature, and optimum inferred score of overall acceptability is 59.6 and 90. Key words: extrdate, overall acceptability, response surface regression analysis, balanced incomplete block method.

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Multiple Regression Technique for Productivity Analysis of the Jointed Plane Concrete Pavement (JPCP)

  • Yoo, Wi-Sung
    • 한국건설관리학회논문집
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    • 제9권6호
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    • pp.268-276
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    • 2008
  • In highway construction projects, concrete pavement productivity has been challenged with constructors and decision-makers; at present there are few methods available to accurately evaluate the factors impacting on it. Any inefficient method to analyze it leads to the excessive schedule, higher rehabilitation costs, shorter service life, and reduction of ride quality. To implement these negative outcomes, constructors or decision-makers need a systematic tool that can be used to categorize the factors related to construction productivity. This paper applies multiple regression technique for productivity analysis of the Jointed Plane Concrete Pavement (JPCP), identifies the significant factors, and provides a predictive model assisting in monitoring and managing the productivity of the JPCP construction process. The completed and progressive projects are employed to derive and assess the proposed model. The results are analyzed to illustrate its capabilities.