• 제목/요약/키워드: regression equation model

검색결과 747건 처리시간 0.026초

미계측유역의 일유출량 추정을 위한 탱크모형 매개변수의 회귀식 산정(수공) (A Regression Equation of Tank Model Parameters for Daily Runoff Estimation in a Region with Insufficient Hydrological Data)

  • 김선주;김필식;윤찬영
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 2000년도 학술발표회 발표논문집
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    • pp.412-418
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    • 2000
  • The purpose of this study is estimation of daily runoff in the watershed with insufficient hydrological data using tank model. In order to estimate, twentysix watersheds were selected to calibrate tank model parameters that were defined by a trial and error method. Results were correlated with characteristics of watershed. Relationships between the parameters and the watershed characteristics were derived by a multiple regression analysis. The simulation results were in agreement with the observed data.

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Statistical analysis on the fluence factor of surveillance test data of Korean nuclear power plants

  • Lee, Gyeong-Geun;Kim, Min-Chul;Yoon, Ji-Hyun;Lee, Bong-Sang;Lim, Sangyeob;Kwon, Junhyun
    • Nuclear Engineering and Technology
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    • 제49권4호
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    • pp.760-768
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    • 2017
  • The transition temperature shift (TTS) of the reactor pressure vessel materials is an important factor that determines the lifetime of a nuclear power plant. The prediction of the TTS at the end of a plant's lifespan is calculated based on the equation of Regulatory Guide 1.99 revision 2 (RG1.99/2) from the US. The fluence factor in the equation was expressed as a power function, and the exponent value was determined by the early surveillance data in the US. Recently, an advanced approach to estimate the TTS was proposed in various countries for nuclear power plants, and Korea is considering the development of a new TTS model. In this study, the TTS trend of the Korean surveillance test results was analyzed using a nonlinear regression model and a mixed-effect model based on the power function. The nonlinear regression model yielded a similar exponent as the power function in the fluence compared with RG1.99/2. The mixed-effect model had a higher value of the exponent and showed superior goodness of fit compared with the nonlinear regression model. Compared with RG1.99/2 and RG1.99/3, the mixed-effect model provided a more accurate prediction of the TTS.

수위-유량관계식에 새로운 양방향 회귀모형의 적용 (An Application of a New Two-Way Regression Model for Rating Curves)

  • 이창해
    • 한국수자원학회논문집
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    • 제41권1호
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    • pp.17-25
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    • 2008
  • 수위-유량관계식의 유도와 실무적용에 있어 통상적으로 회귀분석의 특성을 간과하고 사용하는 경우가 종종 발생한다. 예를 들어 실무에서는 관측수위로부터 관측유량으로 회귀분석되어 만들어진 수위-유량관계식을 홍수모형으로부터 모의된 설계홍수유출량으로부터 설계홍수위를 환산하는데 사용되기도 한다. 그러나 독립과 종속변수가 서로 바뀌면, 관측치와 회귀식간 연직거리의 잔차들로부터 유도된 기존의 회귀분석에 의하여, 회귀식이 서로 달라지기 때문에 역으로 적용하여서는 안 된다. 본 연구에서는 이런 문제점을 해결하기위해 회귀식의 변수들을 상호 교환할 수 있는 최소자승 회귀분석의 새로운 알고리즘을 제안하였다. 새로운 방법을 낙동강유역의 본류 5개 수위표지점의 수위-유량관계식에 대하여 적용하였다. 3가지 회귀식이 유도되었는데, 이들은 각각 수위로부터 유량으로(model 1), 유량으로부터 수위로(model 2) 그리고 양방향(model 3)으로 유도된 수위-유량관계식을 비교하여 실무에서 잘못 적용되는 실수를 줄일 수 있는 새로운 방법을 제시하였다.

회귀방정식과 PID제어기에 의한 DC모터 제어 (DC Motor Control using Regression Equation and PID Controller)

  • 서기영;이수흠;문상필;이내일;최종수
    • 융합신호처리학회 학술대회논문집
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    • 한국신호처리시스템학회 2000년도 하계종합학술대회논문집
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    • pp.129-132
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    • 2000
  • We propose a new method to deal with the optimized auto-tuning for the PID controller which is used to the process -control in various fields. First of all, in this method, initial values of DC motor are determined by the Ziegler-Nichols method. Finally, after studying the parameters of PID controller by input vector of multiple regression analysis, when we give new K, L, T values to multiple regression model, the optimized parameters of PID controller is found by multiple regression analysis program.

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일반화추정방정식(GEE)에 대한 부스트랩의 적용 (Bootstrap Estimation for GEE Models)

  • 박종선;전용문
    • 응용통계연구
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    • 제24권1호
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    • pp.207-216
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    • 2011
  • 본 논문에서는 일반화추정방정식(GEE)모형에 대한 부스트랩 방법의 적용에 대하여 살펴본다. 다양한 부스트랩 방법들 중 GEE모형에 적용이 가능한 잔차, 쌍 및 점수함수 부스트랩 방법을 가상 및 실제 자료들에 적용한 결과 회귀계수들에 대한 추정치와 표준오차가 점근값들과 차이를 보이는 것으로 나타났다. 따라서 표본수가 크지 않은 경우 부스트랩 방법을 통하여 GEE모형에서의 회귀계수에 대한 추정치화 표준편차를 구하는 것이 효과적임을 알 수 있다.

Model to Predict Absorbed Amino Acid Supply at the Proximal Duodenum in Growing Beef Cattle

  • Yan, Xianghua;Xu, Zirong;Zhang, Wen-ju;Wang, Jiaqi
    • Asian-Australasian Journal of Animal Sciences
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    • 제18권3호
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    • pp.358-363
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    • 2005
  • Five crossbred beef cattle (Simmental${\times}$yellow cattle, Shantung Province) fitted with permanent cannulae in the rumen and T-type cannulae at the proximal duodenum and terminal ileum, were fed five different diets containing corn, cotton meal or soybean meal and ammoniated straw to determine the dry matter, crude protein and amino acid flows in duodenal and ileum digesta, and to calculate the regression equations between theoretical and experimental concentration of AA in duodenal digesta. The results showed that there was a strong correlation between experimental (g/d, y) and theoretical CP flows (g/d, x) at the proximal duodenum, the $R^2$-value regression equation of crude protein is very high (0.9636). The $R^2$-value regression equation of the limiting amino acid (such as Met or Lys) is high (0.7573 or 0.9252 respectively). This results indicated that we can formulate better diets fed to beef cattle according to the theoretical amino acid concentration. A mathematical model has been successfully constructed for predicting the supply of absorbed amino acids at the proximal duodenum in growing beef cattle.

Estimating excess post-exercise oxygen consumption using multiple linear regression in healthy Korean adults: a pilot study

  • Jung, Won-Sang;Park, Hun-Young;Kim, Sung-Woo;Kim, Jisu;Hwang, Hyejung;Lim, Kiwon
    • 운동영양학회지
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    • 제25권1호
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    • pp.35-41
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    • 2021
  • [Purpose] This pilot study aimed to develop a regression model to estimate the excess post-exercise oxygen consumption (EPOC) of Korean adults using various easy-to-measure dependent variables. [Methods] The EPOC and dependent variables for its estimation (e.g., sex, age, height, weight, body mass index, fat-free mass [FFM], fat mass, % body fat, and heart rate_sum [HR_sum]) were measured in 75 healthy adults (31 males, 44 females). Statistical analysis was performed to develop an EPOC estimation regression model using the stepwise regression method. [Results] We confirmed that FFM and HR_sum were important variables in the EPOC regression models of various exercise types. The explanatory power and standard errors of estimates (SEE) for EPOC of each exercise type were as follows: the continuous exercise (CEx) regression model was 86.3% (R2) and 85.9% (adjusted R2), and the mean SEE was 11.73 kcal, interval exercise (IEx) regression model was 83.1% (R2) and 82.6% (adjusted R2), while the mean SEE was 13.68 kcal, and the accumulation of short-duration exercise (AEx) regression models was 91.3% (R2) and 91.0% (adjusted R2), while the mean SEE was 27.71 kcal. There was no significant difference between the measured EPOC using a metabolic gas analyzer and the predicted EPOC for each exercise type. [Conclusion] This pilot study developed a regression model to estimate EPOC in healthy Korean adults. The regression model was as follows: CEx = -37.128 + 1.003 × (FFM) + 0.016 × (HR_sum), IEx = -49.265 + 1.442 × (FFM) + 0.013 × (HR_sum), and AEx = -100.942 + 2.209 × (FFM) + 0.020 × (HR_sum).

Hybrid Fuzzy Least Squares Support Vector Machine Regression for Crisp Input and Fuzzy Output

  • Shim, Joo-Yong;Seok, Kyung-Ha;Hwang, Chang-Ha
    • Communications for Statistical Applications and Methods
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    • 제17권2호
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    • pp.141-151
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    • 2010
  • Hybrid fuzzy regression analysis is used for integrating randomness and fuzziness into a regression model. Least squares support vector machine(LS-SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate hybrid fuzzy linear and nonlinear regression models with crisp inputs and fuzzy output using weighted fuzzy arithmetic(WFA) and LS-SVM. LS-SVM allows us to perform fuzzy nonlinear regression analysis by constructing a fuzzy linear regression function in a high dimensional feature space. The proposed method is not computationally expensive since its solution is obtained from a simple linear equation system. In particular, this method is a very attractive approach to modeling nonlinear data, and is nonparametric method in the sense that we do not have to assume the underlying model function for fuzzy nonlinear regression model with crisp inputs and fuzzy output. Experimental results are then presented which indicate the performance of this method.

IT중소기업의 리더십과 임파워먼트에서 MMR과 SEM 검증방법에 따른 팔로워십 조절효과분석 (The moderating effects Analysis of followership according to the MMR & SEM methods to leadership and empowerment in IT SMEs)

  • 이영신;박재성
    • 디지털산업정보학회논문지
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    • 제8권3호
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    • pp.199-212
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    • 2012
  • This study focuses on the influence of followership on leadership and empowerment, and to verify based on the control variables taken in IT SME's to enhance competitiveness through innovation and improvement plan that have been taken. Because there can be a lot of information to be taken, the laws of Moderated Regression Multiple analysis(MMR) were used. Amos, due to the moderating effect of Structural Equation Modeling(SEM) has been employed to re-verify the results seen with Moderated Regression Multiple analysis. The paper focuses on determining whether transformational leadership or transactional leadership is effective as shown by the levels of empowerment derived from these two types of leadership under study. As a result, both the Moderated Regression Multiple analysis and structural equation model searched information on transformational and followership for empowerment having moderating effects. In the Moderated Regression Multiple analysis, results showed that empowerment for leadership in business in the regulation of followership role appeared not to be seen. However, using the structural equation modeling, moderating effects have been found.

Sequential prediction of TBM penetration rate using a gradient boosted regression tree during tunneling

  • Lee, Hang-Lo;Song, Ki-Il;Qi, Chongchong;Kim, Kyoung-Yul
    • Geomechanics and Engineering
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    • 제29권5호
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    • pp.523-533
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    • 2022
  • Several prediction model of penetration rate (PR) of tunnel boring machines (TBMs) have been focused on applying to design stage. In construction stage, however, the expected PR and its trends are changed during tunneling owing to TBM excavation skills and the gap between the investigated and actual geological conditions. Monitoring the PR during tunneling is crucial to rescheduling the excavation plan in real-time. This study proposes a sequential prediction method applicable in the construction stage. Geological and TBM operating data are collected from Gunpo cable tunnel in Korea, and preprocessed through normalization and augmentation. The results show that the sequential prediction for 1 ring unit prediction distance (UPD) is R2≥0.79; whereas, a one-step prediction is R2≤0.30. In modeling algorithm, a gradient boosted regression tree (GBRT) outperformed a least square-based linear regression in sequential prediction method. For practical use, a simple equation between the R2 and UPD is proposed. When UPD increases R2 decreases exponentially; In particular, UPD at R2=0.60 is calculated as 28 rings using the equation. Such a time interval will provide enough time for decision-making. Evidently, the UPD can be adjusted depending on other project and the R2 value targeted by an operator. Therefore, a calculation process for the equation between the R2 and UPD is addressed.