• 제목/요약/키워드: Linear and multiple regression

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MOISTURE CONTENT MEASUREMENT OF POWDERED FOOD USING RF IMPEDANCE SPECTROSCOPIC METHOD

  • Kim, K. B.;Lee, J. W.;S. H. Noh;Lee, S. S.
    • 한국농업기계학회:학술대회논문집
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    • 한국농업기계학회 2000년도 THE THIRD INTERNATIONAL CONFERENCE ON AGRICULTURAL MACHINERY ENGINEERING. V.II
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    • pp.188-195
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    • 2000
  • This study was conducted to measure the moisture content of powdered food using RF impedance spectroscopic method. In frequency range of 1.0 to 30㎒, the impedance such as reactance and resistance of parallel plate type sample holder filled with wheat flour and red-pepper powder of which moisture content range were 5.93∼-17.07%w.b. and 10.87 ∼ 27.36%w.b., respectively, was characterized using by Q-meter (HP4342). The reactance was a better parameter than the resistance in estimating the moisture density defined as product of moisture content and bulk density which was used to eliminate the effect of bulk density on RF spectral data in this study. Multivariate data analyses such as principal component regression, partial least square regression and multiple linear regression were performed to develop one calibration model having moisture density and reactance spectral data as parameters for determination of moisture content of both wheat flour and red-pepper powder. The best regression model was one by the multiple linear regression model. Its performance for unknown data of powdered food was showed that the bias, standard error of prediction and determination coefficient are 0.179% moisture content, 1.679% moisture content and 0.8849, respectively.

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스마트 무인기용 터보축 엔진의 성능진단을 위한 결함 예측에 관한 연구 (A Study on Defect Diagnostics for Health Monitoring of a Turbo-Shaft Engine for SUAV)

  • 박준철;노태성;최동환
    • 한국추진공학회:학술대회논문집
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    • 한국추진공학회 2005년도 제24회 춘계학술대회논문집
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    • pp.248-251
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    • 2005
  • 본 연구에서는 가스 터빈 엔진의 결함에 의해 나타나는 엔진의 성능 저하를 진단하는 기법을 연구하였다. 대상 엔진을 모델화하기 위해 상용 프로그램 GSP를 이용하여 저하된 성능 진단을 위한 변수들을 추출하였으며 이를 바탕으로 Health Monitoring을 위한 Virtual Sensor Model을 구축하였다. 단일 결함과 복합 결함을 예측하기 위한 방법으로 Multiple Linear Regression기법과 가중치를 이용한 기법을 도입하여 엔진 구성품의 결함 위치 및 결함 정도를 예측하였다.

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다중선형회귀모델 기반 고출력 직렬 배터리 팩의 전압 불균형 추정 (Multiple linear regression model-based voltage imbalance estimation for high-power series battery pack)

  • 김승우;이평연;한동호;김종훈
    • 전기전자학회논문지
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    • 제23권1호
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    • pp.1-8
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    • 2019
  • 본 논문에서는 18650 원통형 NCA 리튬이온 배터리로 구성된 고출력 직렬 배터리로 다양한 C-rate의 전기적 특성을 테스트한다. 테스트를 통해 추출한 14S1P 배터리 팩의 방전 용량 데이터와 4S1P 배터리 팩의 EV cycle 데이터를 통해 C-rate의 변화에 따른 전기적 특성을 분석한다. 분석을 통해 얻은 데이터를 기반으로 C-rate에 따른 방전용량 실험의 셀 간 전압 편차와 EV cycle 실험의 셀 간 전압 편차를 다중선형회귀 모델로 추정하여 선형적인 특징을 가진 데이터와 비선형적인 특징을 가진 데이터에 대한 각각의 추정성능을 검증한다. 모델의 추정성능을 검증하기 위해 추정 데이터와 실제 데이터의 RMSE를 구해 알고리즘의 정확성을 평가한다. 논문의 결과는 14S1P 배터리 팩의 방전 용량의 셀 간 전압 불균형과 4S1P 배터리 팩의 EV cycle의 셀 간 전압 불균형 중 선형적인 데이터인 방전 용량의 셀 간 불균형 데이터의 추정 성능이 더 뛰어난 것을 검증하는데 기여한다.

Machine learning-based regression analysis for estimating Cerchar abrasivity index

  • Kwak, No-Sang;Ko, Tae Young
    • Geomechanics and Engineering
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    • 제29권3호
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    • pp.219-228
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    • 2022
  • The most widely used parameter to represent rock abrasiveness is the Cerchar abrasivity index (CAI). The CAI value can be applied to predict wear in TBM cutters. It has been extensively demonstrated that the CAI is affected significantly by cementation degree, strength, and amount of abrasive minerals, i.e., the quartz content or equivalent quartz content in rocks. The relationship between the properties of rocks and the CAI is investigated in this study. A database comprising 223 observations that includes rock types, uniaxial compressive strengths, Brazilian tensile strengths, equivalent quartz contents, quartz contents, brittleness indices, and CAIs is constructed. A linear model is developed by selecting independent variables while considering multicollinearity after performing multiple regression analyses. Machine learning-based regression methods including support vector regression, regression tree regression, k-nearest neighbors regression, random forest regression, and artificial neural network regression are used in addition to multiple linear regression. The results of the random forest regression model show that it yields the best prediction performance.

MULTIPLE OUTLIER DETECTION IN LOGISTIC REGRESSION BY USING INFLUENCE MATRIX

  • Lee, Gwi-Hyun;Park, Sung-Hyun
    • Journal of the Korean Statistical Society
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    • 제36권4호
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    • pp.457-469
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    • 2007
  • Many procedures are available to identify a single outlier or an isolated influential point in linear regression and logistic regression. But the detection of influential points or multiple outliers is more difficult, owing to masking and swamping problems. The multiple outlier detection methods for logistic regression have not been studied from the points of direct procedure yet. In this paper we consider the direct methods for logistic regression by extending the $Pe\tilde{n}a$ and Yohai (1995) influence matrix algorithm. We define the influence matrix in logistic regression by using Cook's distance in logistic regression, and test multiple outliers by using the mean shift model. To show accuracy of the proposed multiple outlier detection algorithm, we simulate artificial data including multiple outliers with masking and swamping.

지역빈도해석 및 다중회귀분석을 이용한 산악형 강수해석 (Orographic Precipitation Analysis with Regional Frequency Analysis and Multiple Linear Regression)

  • 윤혜선;엄명진;조원철;허준행
    • 한국수자원학회논문집
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    • 제42권6호
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    • pp.465-480
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    • 2009
  • 본 연구에서는 다중회귀분석을 이용하여 산악효과를 야기하는 지형인자와 강수와의 관계를 파악하였다. 섬 전체가 산악지형인 제주도의 연평균강수량과 지수홍수법으로 산출한 확률강우량을 강수자료로 사용하여 산악효과를 야기하는 지형인자로 선정한 고도, 위 경도와 회귀모형을 구성하였다. 회귀분석 결과 연평균강수량과 고도와의 선형관계가 확률강우량에서도 동일하게 나타났으며, 고도이외에 위도, 경도를 각각 추가인자로 고려할 경우 강우량과 더욱 강한 상관성을 보였다. 또한, 고도와 위도, 경도를 모두 고려한 회귀모형을 이용한 지형공간분석 결과 제주도의 실제 강수특성과 마찬가지로 남동부로 편중된 강수형태를 보여 모형의 적합성을 증명하였다. 그러나 지속시간 및 재현기간과 무관하게 높은 고도에서 회귀식의 유효성이 감소하므로, 높은 고도에서의 추가적인 산악효과인자의 강수량에 대한 영향이 존재될 것으로 판단되므로 추후 연구가 필요하다.

Particle size distributions and concentrations above radiators in indoor environments: Exploratory results from Xi'an, China

  • Chen, Xi;Li, Angui
    • Environmental Engineering Research
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    • 제20권3호
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    • pp.237-245
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    • 2015
  • Particulate matter in indoor environments has caused public concerns in recent years. The objective of this research is to explore the influence of radiators on particle size distributions and concentrations. The particle size distributions as well as concentrations above radiators and in the adjacent indoor air are monitored in forty-two indoor environments in Xi'an, China. The temperatures, relative humidity and air velocities are also measured. The particle size distributions above radiators at ten locations are analyzed. The results show that the functional difference of indoor environments has little impact on the particle size distributions above radiators. Then the effects of the environmental parameters (particle concentrations in the adjacent indoor air, temperatures, relative humidities and air velocities) on particle concentrations above radiators are assessed by applying multiple linear regression analysis. Three multiple linear regression models are established to predict the concentrations of $PM_{10}$, $PM_{2.5}$ and $PM_1$ above radiators.

The health effects of low blood lead level in oxidative stress as a marker, serum gamma-glutamyl transpeptidase level, in male steelworkers

  • Su-Yeon Lee;Yong-Jin Lee;Young-Sun Min;Eun-Chul Jang;Soon-Chan Kwon;Inho Lee
    • Annals of Occupational and Environmental Medicine
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    • 제34권
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    • pp.34.1-34.13
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    • 2022
  • Background: This study aimed to investigate the association between lead exposure and serum gamma-glutamyl transpeptidase (γGT) levels as an oxidative stress marker in male steelworkers. Methods: Data were collected during the annual health examination of workers in 2020. A total of 1,654 steelworkers were selected, and the variables for adjustment included the workers' general characteristics, lifestyle, and occupational characteristics. The association between the blood lead level (BLL) and serum γGT level was investigated by multiple linear and logistic regression analyses. The BLL and serum γGT values that were transformed into natural logarithms were used in multiple linear regression analysis, and the tertile of BLL was used in logistic regression analysis. Results: The geometric mean of the participants' BLLs and serum γGT level was 1.36 ㎍/dL and 27.72 IU/L, respectively. Their BLLs differed depending on age, body mass index (BMI), smoking status, drinking status, shift work, and working period, while their serum γGT levels differed depending on age, BMI, smoking status, drinking status, physical activity, and working period. In multiple linear regression analysis, the difference in models 1, 2, and 3 was significant, obtaining 0.326, 0.176, and 0.172 (all: p < 0.001), respectively. In the multiple linear regression analysis stratified according to drinking status, BMI, and age, BLLs were positively associated with serum γGT levels. Regarding the logistic regression analysis, the odds ratio of the third BLL tertile in models 1, 2, and 3 (for having an elevated serum γGT level within the first tertile reference) was 2.74, 1.83, and 1.81, respectively. Conclusions: BLL was positively associated with serum γGT levels in male steelworkers even at low lead concentrations (< 5 ㎍/dL).

Multivariate statistical analysis of the comparative antioxidant activity of the total phenolics and tannins in the water and ethanol extracts of dried goji berry (Lycium chinense) fruits

  • Kim, Joo-Shin;Kimm, Haklin Alex
    • 한국식품과학회지
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    • 제51권3호
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    • pp.227-236
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    • 2019
  • Antioxidant activity in water and ethanol extracts of dried Lycium chinense fruit, as a result of the total phenolic and tannin content, was measured using a number of chemical and biochemical assays for radical scavenging and inhibition of lipid peroxidation, with the analysis being extended by applying a bootstrapping statistical method. Previous statistical analyses mostly provided linear correlation and regression analyses between antioxidant activity and increasing concentrations of phenolics and tannins in a concentration-dependent mode. The present study showed that multiple component or multivariate analysis by applying multiple regression analysis or regression planes proved more informative than linear regression analysis of the relationship between the concentration of individual components and antioxidant activity. In this paper, we represented the multivariate analysis of antioxidant activities of both phenolic and tannin contents combined in the water and ethanol extracts, which revealed the hidden observations that were not evident from linear statistical analysis.