• Journal of Cadastre & Land InformatiX
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• v.45 no.2
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• pp.117-130
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• 2015

A least squares method for adjusting the horizontal network satisfies the conditions which is minimizing the sum of the squares of errors based on probability theory. This research compared accuracy of 3rd cadastral control points adjusted by traditional and least square method with respect to the result of Network-RTK. Test results showed the least square method more evenly distribute closure error than traditional method. Mean errors of least square and traditional adjusting method are 2.7cm, 2.2cm respectively. In addition, blunder in angle observations can be detected by comparing position errors which calculated by forward and backward initial coordinates. However, distance blunder cannot offer specific observation line occurred mistake because distance error propagates several observation lines which have similar directions.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.13-16
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• 2008

본 논문은 가중퍼지소속함수 기반신경망(neural network with weighted fuzzy membership functions, NEWFM)기반의 자동 특징 추출기법을 사용하여 인체의 세 방향에서 발생하는 가속도 값으로부터 낙상을 탐지하는 방안을 제시하고 있다. 10명의 피검자로부터 8가지 시나리오로 낙상/비낙상 데이터 800개를 수집하고 웨이블릿 변환(wavelet transform, WT)을 통해 추출한 계수중 비중복면적 분산법에 의해 중요도가 가장 낮은 특징입력을 하나씩 제거하면서 최소의 특징 입력을 선택하였다. 특징입력으로는 가속도 값을 웨이블릿 변환한 11개의 d4계수들 중 비중복면적 분산법에 의해서 중요도가 가장 높은 5개의 계수가 사용되었고, 이들 특징입력을 통해 93%의 전체 분류율을 나타내었다.

• The Transactions of the Korea Information Processing Society
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• v.5 no.9
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• pp.2345-2352
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• 1998

The hyper-geometric distribution software reliability growth model was recently developed and successfully applied Due to mathematical difficultv of the maximum likclihmd method, the least squares method has hem suggested for parameter estimation by the previous studies. We first summarize and compare the minimization criteria adopted by the previous studies. It is theo shown that the weighted least squares method is more appropriate hecause of the nonhomogeneous variability of the number of newly detected faults. The adequacy of the weighted least squares method is illustrated by two numerical examples. Finally, we propose a new method fur predicting the number of faults newly discovered by next test instances. The new prediction method can be used for determining the time to stop testing.

• Journal of the Korean Geophysical Society
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• v.5 no.3
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• pp.233-245
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• 2002

The spectral-analysis-of-surface-waves (SASW) method is a nondestructive testing method based upon generation and detection of elastic stress waves. SASW is widely used as one of the techniques to determine stiffness profile in engineering geophysics. The essential steps involved are construction of an experimental dispersion curve from data collected in situ, and inversion of the dispersion curve to determine the stiffness profile. The main object of this study is to derive an analytical Jacobian for the inversion. If we set the subsurface to N homogeneous layer, it could save 2N times Jacobian calculation compared to numerical jacobian calculation during inversion. To reconstruct a stiffness profile, constrained damped least square method was applied for the inversion. The algorithm was tested for the numerical data and for the real asphalt and tunnel data, which were able to verify the stiffness profile. The stiffness profile reconstructed by the algorithm showed the possibility to appraise the soundness of tunnel with applications SASW.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.1
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• pp.97-105
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• 2015

Multiresponse optimization (MRO) seeks to find the setting of input variables, which optimizes the multiple responses simultaneously. The approach of weighted mean squared error (WMSE) minimization for MRO imposes a different weight on the squared bias and variance, which are the two components of the mean squared error (MSE). To date, a weighted sum-based method has been proposed for WMSE minimization. On the other hand, this method has a limitation in that it cannot find the most preferred solution located in a nonconvex region in objective function space. This paper proposes a Tchebycheff metric-based method to overcome the limitations of the weighted sum-based method.

• Proceedings of the Optical Society of Korea Conference
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• 2009.02a
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• pp.143-144
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• 2009

• Proceedings of the KAIS Fall Conference
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• 2009.05a
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• pp.641-644
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• 2009

일반적으로 신에너지전원(분산전원)이 설치되면, 연계지점 위치와 사고발생 위치에 따라 % 임피던스의 병렬화로 사고전류가 감소하는 분류효과가 발생할 수 있다. 이 때, 보호기기의 최소 정정치 이하로 사고전류가 감소하여 보호기기가 부 동작(동작해야 하는데 동작하지 않은 경우)하는 문제점이 발생한다. 본 연구에서는 현행 분산전원 연계기준 및 선로운영기준을 토대로 어떤 경우에 각 보호기기의 최소 정정치에 미달하는 지 사례 및 최악조건을 제시한다. 본 논문에서는 대칭좌표법을 이용하여 보호기기의 부 동작의 주요 원인이 되는 분류효과에 대한 문제점을 분석하고, 이에 대한 대책방안을 제시한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.599-604
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• 2005

This paper presents fuzzy rules to predict diagnosis of Wisconsin breast cancer with minimized number of feature in put using the neural network with weighted fuzzy membership functions (NEWFM) and the non-overlap area distribution measurement method. NEWFM is capable of self-adapting weighted membership functions from the given the Wisconsin breast cancer clinical training data. n set of small, medium, and large weighted triangular membership functions in a hyperbox are used for representing n set of featured input. The membership functions are randomly distributed and weighted initially, and then their positions and weights are adjusted during learning. After learning, prediction rules are extracted directly from n set of enhanced bounded sums of n set of small, medium, and large weighted fuzzy membership functions. Then, the non-overlap area distribution measurement method is applied to select important features by deleting less important features. Two sets of prediction rules extracted from NEWFM using the selected 4 input features out of 9 features outperform to the current published results in number of set of rules, number of input features, and accuracy with 99.71%.

• Journal of Internet Computing and Services
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• v.10 no.3
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• pp.17-25
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• 2009

This paper presents a methodology for a fall detection using the feature extraction method based on the neural network with weighted fuzzy membership functions (NEWFM). The distributed non-overlap area measurement method selects the minimized number of input features by removing the worst input features one by one. Nineteen number of wavelet transformed coefficients captured by a triaxial accelerometer are selected as minimized features using the non-overlap area distribution measurement method. The proposed methodology shows that sensitivity, specificity, and accuracy are 95%, 97.25%, and 96.125%, respectively.

• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.423-429
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• 2014

This paper discusses a method for getting Type I sums of squares by projections under a two-way fixed-effects model when variances of errors are not equal. The method of weighted least squares is used to estimate the parameters of the assumed model. The model is fitted to the data in a sequential manner by using the model comparison technique. The vector space generated by the model matrix can be composed of orthogonal vector subspaces spanned by submatrices consisting of column vectors related to the parameters. It is discussed how to get the Type I sums of squares by using the projections into the orthogonal vector subspaces.