• Title/Summary/Keyword: curve estimation

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Curvature Estimation Method of Curve Section Using Relative Displacement Between Body and Bogie of Rolling-stock (철도차량 차체/대차간 상대변위를 이용한 곡선구간 곡률반경 추정 방법)

  • Hur, Hyun-Moo;Park, Joon-Hyuk;You, Won-Hee
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.36 no.11
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    • pp.1479-1485
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    • 2012
  • The development of a technique for the real-time sensing of a curve section is very important for active rolling-stocks in order to improve the curving performance. However, conventional methods using expensive track inspection equipment or various complex sensors are not practicable to be applied to commercial vehicles. Therefore, we have proposed a new method to estimate the curve radius of a curve section. This method uses the relative displacements occurring between the body and the bogie when the rolling-stock is running on a curve. To verify the validity of this method, we conducted a vehicle dynamics simulation and test using a real vehicle on a test line. The results confirmed the validity of the proposed method. We expect that this method will be effectively applied in studies of active rolling-stocks to increase the curving performance using active control technology.

NONPARAMETRIC MAXIMUM LIKELIHOOD ESTIMATION OF A CONCAVE RECEIVER OPERATING CHARACTERISTIC CURVE VIA GEOMETRIC PROGRAMMING

  • Lee, Kyeong-Eun;Lim, Johan
    • Bulletin of the Korean Mathematical Society
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    • v.48 no.3
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    • pp.523-537
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    • 2011
  • A receiver operating characteristic (ROC) curve plots the true positive rate of a classier against its false positive rate, both of which are accuracy measures of the classier. The ROC curve has several interesting geometrical properties, including concavity which is a necessary condition for a classier to be optimal. In this paper, we study the nonparametric maximum likelihood estimator (NPMLE) of a concave ROC curve and its modification to reduce bias. We characterize the NPMLE as a solution to a geometric programming, a special type of a mathematical optimization problem. We find that the NPMLE is close to the convex hull of the empirical ROC curve and, thus, has smaller variance but positive bias at a given false positive rate. To reduce the bias, we propose a modification of the NPMLE which minimizes the $L_1$ distance from the empirical ROC curve. We numerically compare the finite sample performance of three estimators, the empirical ROC curve, the NMPLE, and the modified NPMLE. Finally, we apply the estimators to estimating the optimal ROC curve of the variance-threshold classier to segment a low depth of field image and to finding a diagnostic tool with multiple tests for detection of hemophilia A carrier.

Estimation of Runoff Curve Number for Chungju Dam Watershed Using SWAT (SWAT을 이용한 충주댐 유역의 유출곡선지수 산정 방안)

  • Kim, Nam-Won;Lee, Jin-Won;Lee, Jeong-Woo;Lee, Jeong-Eun
    • Journal of Korea Water Resources Association
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    • v.41 no.12
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    • pp.1231-1244
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    • 2008
  • The objective of this study is to present a methodology for estimating runoff curve number(CN) using SWAT model which is capable of reflecting watershed heterogeneity such as climate condition, land use, soil type. The proposed CN estimation method is based on the asymptotic CN method and particularly, it uses surface flow data simulated by SWAT. This method has advantages to estimate spatial CN values according to subbasin division and to reflect watershed characteristics because the calibration process has been made by matching the measured and simulated streamflows. Furthermore, the method is not sensitive to rainfall-runoff data since CN estimation is on a daily basis. The SWAT based CN estimation method is applied to Chungju dam watershed. The regression equation of the estimated CN that exponentially decays with the increase of rainfall is presented.

EFFICIENT ESTIMATION OF THE REGULARIZATION PARAMETERS VIA L-CURVE METHOD FOR TOTAL LEAST SQUARES PROBLEMS

  • Lee, Geunseop
    • Journal of the Korean Mathematical Society
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    • v.54 no.5
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    • pp.1557-1571
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    • 2017
  • The L-curve method is a parametric plot of interrelation between the residual norm of the least squares problem and the solution norm. However, the L-curve method may be hard to apply to the total least squares problem due to its no closed form solution of the regularized total least squares problems. Thus the sequence of the solution norm under the fixed regularization parameter and its corresponding residual need to be found with an efficient manner. In this paper, we suggest an efficient algorithm to find the sequence of the solutions and its residual in order to plot the L-curve for the total least squares problems. In the numerical experiments, we present that the proposed algorithm successfully and efficiently plots fairly 'L' like shape for some practical regularized total least squares problems.

On the estimation of parameters for the growth curve of the Korean Population (한국의 인구곡선 추정에 관한 연구)

  • 구자흥
    • The Korean Journal of Applied Statistics
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    • v.7 no.2
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    • pp.249-261
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    • 1994
  • The purpose of this research is to obtain a Simple Logistic Curve for the curve fitting of Korean total Population. Based on the population census data from 1949 to 1990, the parameters are estimated by 3-group method. As the results, intercensal populations of Korea from 1950 to 190 are estimated, and Korean total populations from 1991 to 2010 A.D. are projected. And we also can suggest the upper asymptote 58, 616 thousands of Korean total population.

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Design Wave Period Estimation Using the Wave Height Information (파고 정보를 이용한 설계주기 추정)

  • Hong-Yeon Cho;Weon Mu Jeong;Ju Whan Kang;Gi-Seop Lee
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.35 no.4
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    • pp.84-94
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    • 2023
  • The wave height and period regression curve is widely used to estimate the design wave period. In this study, the parameters of the curves are estimated, compared, and evaluated using the linear, robust linear, and nonlinear regression methods, respectively. The data used in the design wave height estimation are the annual maxima (AM) wave height and period data sets divided by typhoon and non-typhoon conditions, provided by the Ministry of Oceans and Fisheries (2019). The estimation parameters show significant differences in the local coastal waters and the estimation methods. The estimation parameters based on the Suh et al. (2008, 2010) method show the apparent bias, under-estimation in the intercept (scale) parameter, and over-estimation in the slope (exponent) parameter, respectively.

Estimation Method of Strain Distribution for Safety Monitoring of Multi-span Steel Beam Using FBG Sensor (FBG센서를 이용한 다경간 강재 보 구조물의 안전성 모니터링을 위한 변형률 분포 추정 기법)

  • Oh, Byung-Kwan;Lee, Ji-Hoon;Choi, Se-Woon;Park, Hyo-Seon;Kim, You-Sok
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.18 no.1
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    • pp.138-149
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    • 2014
  • This study proposes an estimation method of strain distribution for multi-span steel beam structure under unspecific loading conditions. The estimation method in this paper employs the curve fitting using the least square method from measured strain data, not analytical method. To verify the proposed estimation method, a static loading test for multi-span steel beam on which distributed and concentrated loads act was conducted. The strain data for verification was measured by FBG sensors that have multiplexing technology. The analysis of the accuracy of strain estimation for distributed and concentrated loads and the errors by considering the number of measured points used in the estimation were conducted. In the maximum strain points, the strains could be estimated with the errors of 5.89% (loading step 1) and 6.26% (loading step 2). In case of decreasing the number of sensors, it was also confirmed that the errors increased (0.26~0.37%). Through the curve fitting method, it is possible to estimate the strain distribution (maximum strains and their locations) of multi-span beam for unspecific loads and go over the limit of the analytical estimation method which is suitable for specific distributed loads.

Parameter Estimation of Intensity-Duration-Frequency Curve Using Genetic Algorithm (I): Comparison Study of Existing Estimation Method (유전자알고리즘을 이용한 강우강도식 매개변수 추정에 관한 연구(I): 기존 매개변수 추정방법과의 비교)

  • Kim, Tae-Son;Shin, Ju-Young;Kim, Soo-Young;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.40 no.10
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    • pp.811-821
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    • 2007
  • The intensity-duration-frequency (IDF) curves by Talbot, Sherman and Japanese type formulas are widely used in South Korea since the parameters are easily estimated. However, these IDF curves' accuracies are relatively worse than those of the IDF curves developed by Lee et al. (1993) and Heo et al. (1999), and different parameters for the given return periods should be computed. In this study, parameter estimation method for the IDF curve by Heo et al. (1999) is suggested using genetic algorithm (GA). Quantiles computed by at-site frequency analysis using the rainfall data of 22 rainfall gauges operated by Korea Meteorological Administration are employed to estimate the parameters of IDF curves and minimizing root mean squared error (RMSE) and relative RMSE (RRMSE) of observed and computed quantiles are used as objective functions of GA. The comparison of parameter estimation methods between the empirical regression analysis and the suggested method show that the IDF curve in which the parameters are estimated by GA using RRMSE as an objective function is superior to the IDF curves using RMSE.

Pollutant Loading Estimates from Watershed by Rating Curve Method and SWMM

  • Jeon, Ji-Hong;Yoon, Chun-Gyeong
    • Korean Journal of Environmental Agriculture
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    • v.19 no.5
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    • pp.419-425
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    • 2000
  • Rating curve method and SWMM (Storm Water Management Model) were applied to estimate pollutant loading from Hwa-Ong watershed in Kyunggi-Do. Rating curves were derived from sampling sites and applied to the whole watershed. SWMM version 4.4 was calibrated by field data of sampling sites and applied to the whole watershed. The pollutant loading estimated by rating curve was slightly higher than the one by SWMM, but the difference was not significant considering diffuse pollution characteristics of wide variation. Land use effect of the subcatchments could not be incorporated logically in rating curve method and difficulty in extrapolation was experienced, therefore, the estimate by rating curve method was thought to be less confident. SWMM was satisfactory in estimation of pollution loading, and its great flexibility worked well to describe complex nonurban land uses. Neither of them could exactly describe complex natural phenomena, but SWMM was preferred in this study due to its flexibility and logical hydrologic processes including land use effects. Use of reasonable watershed model rather than rating curve method for watershed pollutant loading estimate can be more practical and is recommended.

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