• Proceedings of the Korean Geotechical Society Conference
• /
• 2006.03a
• /
• pp.338-347
• /
• 2006

연직차수벽은 오염지역이나 폐기물 매립장에서 오염된 지하수 (때로는 오염된 수증기) 흐름을 차단하거나 또는 오염지역의 정화처리시 효율을 높이기 위하여 외부로부터 지하수 흐름을 막기 위해 설치된다. 이 논문에서는 연직차수벽의 가장 중요한 설계요소인 차수벽체의 현장 투수성을 평가하는 방법들중 가장 보편적으로 사용되는 단공식 순간 변위시험 (slug test)을 소개한다. 연직차수벽에서 실행된 단공식 순간 변위시험 결과를 해석하기 위해서, 연직차수벽의 압축성과 기하학적인 특성을 고려한 수정된 linear curve fitting 방법을 제안하고 그 적용성을 case study를 통해 평가한다. 기존의 대수층 투수계수 산정에 이용된 curve fitting 방법들에 비하여 수정된 linear curve fitting 방법은 보다 정확한 연직차수벽체의 투수성을 평가하도록 한다.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.20 no.3
• /
• pp.17-29
• /
• 1995

Recently, neural network models have been employed as an alternative to regression analysis for point estimation or function fitting in various field. Thus far, however, no theoretical or empirical guides seem to exist for selecting the tool which the most suitable one for a specific function-fitting problem. In this paper, we evaluate performance of three major function-fitting techniques, regression analysis and two neural network models, back-propagation and linear-Hebbian-learning neural networks. The functions to be fitted are simple linear ones of a single independent variable. The factors considered are size of noise both in dependent and independent variables, portion of outliers, and size of the data. Based on comutational results performed in this study, some guidelines are suggested to choose the best technique that can be used for a specific problem concerned.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1994.04a
• /
• pp.147-147
• /
• 1994

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.20 no.12
• /
• pp.1333-1339
• /
• 2009

A MWR(Missile Warning Radar) of GVES(Ground Vehicle Equipment System) has to effectively decide the threat for a detected target. Linear Approximation Fitting(LAF) and Weighted Linear Approximation Fitting(WLAF) algorithm is proposed as algorithm for a threat decision method. The target is classified into a threat or non-threat using a boundary condition of the angular rate, and the boundary condition is determined using probability model simulation. This paper confirms the performance of proposed threat decision algorithm using measurement.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.12
• /
• pp.2265-2267
• /
• 2007

The purpose of this work is to compare the local fitting and global fitting approaches while applying regression model to the PTT-BP data for the prediction of exercise blood pressures. We used linear and nonlinear regression models to represent the PTT-BP relationship during exercise. PTT-BP data were acquired both under resting state and also after cycling exercise with several load conditions. PTT was calculated as the time between R-peak of ECG and the peak of differential photo-plethysmogram. For the identification of the regression models, we used local fitting which used only the resting state data and global fitting which used the whole region of data including exercise BP. The results showed that the global fitting was superior to the local fitting in terms of the coefficient of determination and the RMS (root mean square) error between the experimental and estimated BP. The nonlinear regression model which used global fitting showed slightly better performance than the linear one (no significant difference). We confirmed that the wide-range of data is required for the regression model to appropriately predict the exercise BP.

• Journal of the Korean Geotechnical Society
• /
• v.23 no.11
• /
• pp.99-107
• /
• 2007

The linear curve fitting methods such as the Hvorslev method and the Bouwer and Rice method provide a rapid and simple means to analyze slug test data for estimating in-situ hydraulic conductivity (k) of geologic material. However, when analyzing a slug test in a relatively compressible aquifer, these methods have difficulties in fitting a straight line to the semi-logarithmic plot of the test data that shows a concave-upward curvature because the linear curve fitting methods ignore the role of the compressibility or specific storage ($S_s$) of an aquifer. The comparison of the Hvorslev method and the Bouwer and Rice method is made far a partially-penetrating well geometry to show analytically that the Hvorslev method estimates higher hydraulic conductivity than the Bouwer and Rice method except that the well intake section locates very close to the bottom of the aquifer. The effect of fitting a straight line to the slug test data is evaluated along with the dimensionless compressibility parameter (${\alpha}$) ranging from 0.001 to 1. A modified linear curve fitting method that is expanded from Chirlin's approach to the case of a partially penetrating well with the basic-time-lag fitting method is introduced. A case study for a compressible glacial till is made to verify the proposed method by comparing with a type curve method (KGS method).

• The Korean Journal of Applied Statistics
• /
• v.24 no.5
• /
• pp.759-768
• /
• 2011

Tree algorithms have been widely developed for regression problems. One of the good features of a regression tree is the flexibility of fitting because it can correctly capture the nonlinearity of data well. Especially, data with sudden structural breaks such as the price of oil and exchange rates could be fitted well with a simple mixture of a few piecewise linear regression models. Now that split points are determined by chi-squared statistics related with residuals from fitting piecewise linear models and the split variable is chosen by an objective criterion, we can get a quite reasonable fitting result which goes in line with the visual interpretation of data. The piecewise linear regression by a regression tree can be used as a good fitting method, and can be applied to a dataset with much fluctuation.

• Journal of applied mathematics & informatics
• /
• v.8 no.2
• /
• pp.641-649
• /
• 2001

A procedure of detecting change-points is considered with split linear fitting idea from Hall and Titterington(1992). At each given point, left, central and right linear fits are compared to detect the discontinuities or change-points. A simulation study is done with various types of change models and shows that the suggested technique can be a flexible data-analytic tool.

• Communications of the Korean Mathematical Society
• /
• v.21 no.2
• /
• pp.397-407
• /
• 2006

We construct polynomial-fitting interpolation rules to agree with a function f and its first derivative f' at equally spaced nodes on the interval of interest by introducing a linear functional with which we produce systems of linear equations. We also introduce a matrix whose determinant is not zero. Such a property makes it possible to solve the linear systems and then leads to a conclusion that the rules are uniquely determined for the nodes. An example is investigated to compare the rules with Hermite interpolating polynomials.

• Journal of the Korean Magnetic Resonance Society
• /
• v.9 no.2
• /
• pp.93-102
• /
• 2005

Purpose: To develop an advanced non-linear curve fitting (NLCF) algorithm for dynamic susceptibility contrast study of brain. Materials and Methods: The first pass effects give rise to spuriously high estimates of $K^{trans}$ in voxels with large vascular components. An explicit threshold value has been used to reject voxels. Results: By using this non-linear curve fitting algorithm, the blood perfusion and the volume estimation were accurately evaluated in T2*-weighted dynamic contrast enhanced (DCE)-MR images. From the recalculated each parameters, perfusion weighted image were outlined by using modified non-linear curve fitting algorithm. This results were improved estimation of T2*-weighted dynamic series. Conclusion: The present study demonstrated an improvement of an estimation of kinetic parameters from dynamic contrast-enhanced (DCE) T2*-weighted magnetic resonance imaging data, using contrast agents. The advanced kinetic models include the relation of volume transfer constant $K^{trans}\;(min^{-1})$ and the volume of extravascular extracellular space (EES) per unit volume of tissue $\nu_e$.