• Title/Summary/Keyword: Least Square Regression

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Anthocyanins in 'Cabernet Gernischet' (Vitis vinifera L. cv.) Aged Red Wine and Their Color in Aqueous Solution Analyzed by Partial Least Square Regression

  • Han, Fu-Liang;Jiang, Shou-Mei;He, Jian-Jun;Pan, Qiu-Hong;Duan, Chang-Qing;Zhang, Ming-Xia
    • Food Science and Biotechnology
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    • v.18 no.3
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    • pp.724-731
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    • 2009
  • Anthocyanins are considered one of the main color determinants in aged red wine. The anthocyanins in aged red wine made from 'Cabernet Gernischet' (Vitis vinifera L. cv.) grape were investigated by high performance liquid chromatography- electronic spray ionization- mass spectrometry (HPLC-ESI-MS) and their color presented in aqueous solution were evaluated using partial least square regression (PLS). The results showed that there were 37 anthocyanins identified in this wine, including 22 pyranoanthocyanins. The analysis of PLS indicated that different anthocyanins showed distinct color values: malvidin 3-O-(6-O-acetyl)-glucoside-4-vinylguaiacol (Mv3-acet-glu-vg) presented the highest color values, while malvidin 3-O-glucoside (Mv3-glu) showed least. Among the free non-acylated anthocyanins, peonidin 3-O-oglucoside (Pn3-glu) showed the highest color values; the coumarylated anthocyanins presented higher color values than their corresponding acetylated anthocyanins and parent anthocyanins; pyranoanthocyanins presented also higher color values than their original anthocyanins; the color of anthocyanins depended on their structure. This work will be helpful to reveal evolution in aged red wine.

Determination of Urban-Life Housing Price and Return Ratio by Location (도시형생활주택의 입지별 분양가격 및 수익률 결정요인)

  • Park, Jin-A;Woo, Chul-Min;Baik, Min-Seok;Shim, Gyo-Eon
    • The Journal of the Korea Contents Association
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    • v.12 no.11
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    • pp.469-481
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    • 2012
  • The demand for small-sized housing has been increasing due to the recession of real-estate price and the increase of small-sized households. Especially, the demand for affordable housing has been increasing since the style of housing and the location fits the lifestyle of small-sized household. In addition, many investors have been buying it because it has advertised as an investment property holding high-return ratio. However, an empirical analysis about the selling price and the return ratio has not been done yet. Therefore, the purpose of the research is having the empirical analysis based on the selling price and return ration by examining the affordable housing in Seoul. The urban-life housing more than 50 generations of the Seoul was irradiated for the analysis. And the linear regression analysis and PLS(Partial Least Square Regression) analysis was used for the empirical analysis. The result of analysis, based on the linear regression analysis, showed that factors including neighboring housing price and subway catchment area have a significant effect to the determinant factors of housing price. The analysis for return ratio showed neighboring housing price, subway catchment area and amenities affects the ratio. Especially, the fault of using small sample was covered by using the partial least square regression in this research.

Model of Least Square Support Vector Machine (LSSVM) for Prediction of Fracture Parameters of Concrete

  • Kulkrni, Kallyan S.;Kim, Doo-Kie;Sekar, S.K.;Samui, Pijush
    • International Journal of Concrete Structures and Materials
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    • v.5 no.1
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    • pp.29-33
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    • 2011
  • This article employs Least Square Support Vector Machine (LSSVM) for determination of fracture parameters of concrete: critical stress intensity factor ($K_{Ic}^s$) and the critical crack tip opening displacement ($CTOD_c$). LSSVM that is firmly based on the theory of statistical learning theory uses regression technique. The results are compared with a widely used Artificial Neural Network (ANN) Models of LSSVM have been developed for prediction of $K_{Ic}^s$ and $CTOD_c$, and then a sensitivity analysis has been performed to investigate the importance of the input parameters. Equations have been also developed for determination of $K_{Ic}^s$ and $CTOD_c$. The developed LSSVM also gives error bar. The results show that the developed model of LSSVM is very predictable in order to determine fracture parameters of concrete.

A Nonparametric Test for the Parallelism of Regression Lines Based on Kendall's Tau (Kendall의 Tau에 의한 회귀직선의 평행성에 관한 비모수 검정)

  • Song, Moon-Sup
    • Journal of the Korean Statistical Society
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    • v.7 no.1
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    • pp.17-26
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    • 1978
  • For testing $\beta_i=\beta, i=1,...,k$, in the regression model $Y_{ij} = \alpha_i + \beta_ix_{ij} + e_{ij}, j=1,...,n_i$, a simple and robust test based on Kendall's tau is proposed. Its asymptotic distribution is proved to be chi-square under the null hypthesis and noncentral chi-square under an appropriate sequence of alternatives. For the optimal designs, the asymptotic relative efficiency of the proposed procedure with respect to the least squares procedure is the same as that of the Wilcoxon test with respect to the t-test.

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Asymptotic Properties of Least Square Estimator of Disturbance Variance in the Linear Regression Model with MA(q)-Disturbances

  • Jong Hyup Lee;Seuck Heum Song
    • Communications for Statistical Applications and Methods
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    • v.4 no.1
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    • pp.111-117
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    • 1997
  • The ordinary least squares estimator $S^2$ for the variance of the disturbances is considered in the linear regression model with sutocorrelated disturbances. It is proved that the OLS-estimator of disturbance variance is asymptotically unbiased and weakly consistent, when the distrubances are generated by an MA(q) process. In particular, the asymptotic unbiasedness and consistency of $S^2$ is satisfied without any restriction on the regressor matrix.

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Structural design of Optimized Interval Type-2 FCM Based RBFNN : Focused on Modeling and Pattern Classifier (최적화된 Interval Type-2 FCM based RBFNN 구조 설계 : 모델링과 패턴분류기를 중심으로)

  • Kim, Eun-Hu;Song, Chan-Seok;Oh, Sung-Kwun;Kim, Hyun-Ki
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.4
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    • pp.692-700
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    • 2017
  • In this paper, we propose the structural design of Interval Type-2 FCM based RBFNN. Proposed model consists of three modules such as condition, conclusion and inference parts. In the condition part, Interval Type-2 FCM clustering which is extended from FCM clustering is used. In the conclusion part, the parameter coefficients of the consequence part are estimated through LSE(Least Square Estimation) and WLSE(Weighted Least Square Estimation). In the inference part, final model outputs are acquired by fuzzy inference method from linear combination of both polynomial and activation level obtained through Interval Type-2 FCM and acquired activation level through Interval Type-2 FCM. Additionally, The several parameters for the proposed model are identified by using differential evolution. Final model outputs obtained through benchmark data are shown and also compared with other already studied models' performance. The proposed algorithm is performed by using Iris and Vehicle data for pattern classification. For the validation of regression problem modeling performance, modeling experiments are carried out by using MPG and Boston Housing data.

Fast Simulation of Output Voltage for High-Shock Piezoresistive Microaccelerometer Using Mode Superposition Method and Least Square Method (모드중첩법 및 최소자승법을 통한 고충격 압저항 미소가속도계의 출력전압 해석)

  • Han, Jeong-Sam;Kwon, Ki-Beom
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.7
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    • pp.777-787
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    • 2012
  • The transient analysis for the output voltage of a piezoresistive microaccelerometer takes a relatively high computation time because at least two iterations are required to calculate the piezoresistive-structural coupled response at each time step. In this study, the high computational cost for calculating the transient output voltage is considerably reduced by an approach integrating the mode superposition method and the least square method. In the approach, data on static displacement and output voltage calculated by piezoresistive-structural coupled simulation for three acceleration inputs are used to develop a quadratic regression model, relating the output voltage to the displacement at a certain observation point. The transient output voltage is then approximated by a regression model using the displacement response cheaply calculated by the mode superposition method. A high-impact microaccelerometer subject to several types of acceleration inputs such as 100,000 G shock, sine, step, and square pulses are adopted as a numerical example to represent the efficiency and accuracy of the suggested approach.

Effect of Change of Grinding Force on Geometric Error (연삭력 변화량이 공작물의 형상오차에 미치는 영향)

  • Chi, Long-Zhn;Lee, Sang-Jin;Park, Hoo-Myung;Oh, Sang-Lok;Ha, Man-Kyung
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.3 no.2
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    • pp.10-17
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    • 2004
  • A real depth of cut in deformed zone has larger than an ideal depth of cut. So the heat generated during grinding operation makes the deformation of a workpiece surface as convex farm. Consequently the workpiece surface remains a geometric error as concave form after cooling In this study, the grinding force and the geometric error were examined in surface grinding. Through magnitude and mode of geometric error were evaluated according to grinding conditions, an optimal grinding condition was proposed to minimize the geometric error In addition, the relationship between the geometric error and the grinding force was examined. Due to least square regression, It was possible to predict the geometric error by using the grinding force.

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Geometric Error Prediction of Ground Surface by Using Grinding Force (연삭력을 이용한 공작물의 형상오차 예측)

  • 하만경;지용주;곽재섭
    • Transactions of the Korean Society of Machine Tool Engineers
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    • v.13 no.2
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    • pp.9-16
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    • 2004
  • Because a generated heat during grinding operation makes a serious deformation on a ground surface as a convex form, a real depth of cut in deformed zone has larger than an ideal depth of cut. Consequently, the ground surface has a geometric error as a concave form after cooling the workpiece. In this study, the force and the geometric error of surface grinding were examined. From evaluating magnitude and mode of the geometric error according to grinding conditions, an optimal grinding condition was proposed to minimize the geometric error. In addiction the relationship between the geometric error and the grinding force was found out. Due to least square regression it was able to predict the geometric error by using the grinding force.

Nondestructive Quantification of Intact Ambroxol Tablet using Near-infrared Spectroscopy (근적외분광분석법을 사용한 암브록솔 정제의 비파괴적 정량분석)

  • 임현량;우영아;김도형;김효진;강신정;최현철;최한곤
    • YAKHAK HOEJI
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    • v.48 no.1
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    • pp.60-64
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    • 2004
  • Near-infrared (NIR) spectroscopy was used to determine rapidly and nondestructively the content of ambroxol in intact ambroxol tablets containing 30 mg (12.5% m/m nominal concentration) by collecting NIR spectra in range 1100-1750 nm. The laboratory-made samples had 10.3∼15.9% m/m nominal ambroxol concentration. The measurements were made by reflection using a fiber-optic probe and calibration was carried out by partial least square regression (PLSR) with autoscaling. Model validation was performed by randomly splitting the data set into calibration and validation data set (7 samples as a calibration data set and 5 samples as a validation data set). The developed NIR method gave results comparable to the known values of tablets in a laboratorial manufacturing Process, standard error of calibration (SEC) and standard error of prediction (SEP) being 0.49% and 0.49% m/m respectively. The method showed good accuracy and repeatability NIR spectroscopic determination in intact tablets allowed the potential use of real time monitoring for a running production process.