• Journal of the Korean Statistical Society
• /
• v.16 no.1
• /
• pp.21-25
• /
• 1987

The combined estimator of inter- and intra-block estimators in incomplete block designs can be expressed as a weighted average of two location estimators. The weight should be between 0 and 1. However, the negative variance component estimate could result in the weight being negative or larger than 1. In this paper, we show that if two location estimators have symmetric unimodal distributions, truncating the weight to 0 or 1 accordingly improves the combined estimator under an arbitrary convex loss function.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• autumn
• /
• pp.478-481
• /
• 2002

In these days, Cost and Scheduling was managed effectively because of introduction of EVMS to construction project. However the EVMS is appropriate methods to advanced country, so it is difficult to apply into domestic construction project. in this paper weighted value n, m was used of compositive index(CI) to forecast Estimate At Completion (EAC) using statistical analysis in credible interval the objective of this paper is to verify compositive index(CI) and to forecast Estimate At Completion (EAC).

• Proceedings of the KIEE Conference
• /
• 2006.10c
• /
• pp.588-590
• /
• 2006

Recently, many on-line approaches to instrument channel surveillance (drift monitoring and fault detection) have been reported worldwide. On-line monitoring (OLM) method evaluates instrument channel performance by assessing its consistency with other plant indications through parametric or non-parametric models. The heart of an OLM system is the model giving an estimate of the true process parameter value against individual measurements. This model gives process parameter estimate calculated as a function of other plant measurements which can be used to identify small sensor drifts that would require the sensor to be manually calibrated or replaced. This paper describes an improvement of auto-associative kernel regression by introducing a correlation coefficient weighting on kernel distances. The prediction performance of the developed method is compared with conventional auto-associative kernel regression.

• Proceedings of the IEEK Conference
• /
• 1999.11a
• /
• pp.617-620
• /
• 1999

In this paper, a new autofocusing technique which is resistive to noise generated by the CCD of video cameras is proposed. In the proposed scheme, the frequency selective weighted median (FSWM) filter is utilized to estimate the degree of focus and the fast hill-climbing search (HCS) strategy is exploited to determine the best focused image. Since the FSWM filter can not only extract high frequency components from the image, but also eliminate impulsive noise, the proposed autofocusing method employing the FSWM criterion function can estimate the degree of focus precisely. Furthermore, the proposed real-time HCS algorithm enables the video camera to continuously focus on dynamic images. Experimental results demonstrate that the proposed technique outperforms existing techniques by enhancing the accuracy of the focus value of the video camera without the influence of noise.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2007.05a
• /
• pp.1798-1802
• /
• 2007

The practice of business estimate flood discharge by rainfall-flow relation that is easy collection of observation data. The important factor is rainfall, coefficient of runoff, and drainage area for analysis of runoff-flow relation.The practice of business usually use probability rainfall that use a weighted average value after each observation post estimate probability of non-same time. It has more error than same time probability rainfall, and it can excess of estimation because it can't consider space distribution of rainfall.The study of result showed similar aspect with existing ARF but width of coefficient become smaller. And the comparison of peak flow did not different what used by ARF and same time probability rainfall(A group). But non-same time probability rainfall is bigger 25% more than another(B group). Between A group and B group of the difference increased with the lapse of time.

• Journal of Industrial Technology
• /
• v.27 no.A
• /
• pp.95-102
• /
• 2007

The practice of business estimate flood discharge by rainfall-flow relation that is easy collection of observation data. The important factor is rainfall, coefficient of runoff, and drainage area for analysis of runoff-flow relation. The practice of business usually use probability rainfall that use a weighted average value after each observation post estimate probability of non-same time. It has more error than same time probability rainfall, and it can excess of estimation because it can't consider space distribution of rainfall. The study of result showed similar aspect with existing ARF but width of coefficient become smaller. And the comparison of peak flow did not different what used by ARF and same time probability rainfall(A group). But non-same time probability rainfall is bigger 25% more than another(B group). Between A group and B group of the difference increased with the lapse of time.

• Journal of the Korean Mathematical Society
• /
• v.56 no.1
• /
• pp.239-263
• /
• 2019

The $Calder{\acute{o}}n$-Zygmund type estimate is proved for elliptic obstacle problems in bounded non-smooth domains. The problems are related to divergence form nonlinear elliptic equation with measurable nonlinearities. Precisely, nonlinearity $a({\xi},x_1,x^{\prime})$ is assumed to be only measurable in one spatial variable $x_1$ and has locally small BMO semi-norm in the other spatial variables x', uniformly in ${\xi}$ variable. Regarding non-smooth domains, we assume that the boundaries are locally flat in the sense of Reifenberg. We also investigate global regularity in the settings of weighted Orlicz spaces for the weak solutions to the problems considered here.

• Knowledge Management Research
• /
• v.6 no.1
• /
• pp.19-32
• /
• 2005

The reliability of technology valuation depends on, among other things, the reliability of the discount rate estimate. The weighted average cost of capital, generally accepted as discount rate, consists of cost of equity and cost of debt. The model used to estimate the cost of equity for publicly traded firms can not be used directly for small-sized venture firms. In addition, the estimation of cost of debt become very difficult, given the limited and volatile price history, because these small-sized venture firms do not have associated credit ratings. Since two kinds of cost of capital for the small-sized venture firms can not be estimated directly from market data, this study suggests statistical frame works for estimating unknown two kinds of cost of capital. The estimates of underlying cost of capital will help determine the size of appropriate discount rate with logical and scientific way when the technology valuation for small-sized venture firms is made. This study also suggests the necessity of the risk premium for the technology competitiveness to improve the estimation of the appropriate discount rate for small-sized venture firms.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.4
• /
• pp.534-540
• /
• 2014

In this paper, we propose a fuzzy combined Polynomial Neural Network(PNN) for pattern classification. The fuzzy combined PNN comes from the generic TSK fuzzy model with several linear polynomial as the consequent part and is the expanded version of the fuzzy model. The proposed pattern classifier has the polynomial neural networks as the consequent part, instead of the general linear polynomial. PNNs are implemented by stacking the simple polynomials dynamically. To implement one layer of PNNs, the various types of simple polynomials are used so that PNNs have flexibility and versatility. Although the structural complexity of the implemented PNNs is high, the PNNs become a high order-multi input polynomial finally. To estimate the coefficients of a polynomial neuron, The weighted linear discriminant analysis. The output of fuzzy rule system with PNNs as the consequent part is the linear combination of the output of several PNNs. To evaluate the classification ability of the proposed pattern classifier, we make some experiments with several machine learning data sets.

• Journal of the Korean Data and Information Science Society
• /
• v.26 no.4
• /
• pp.907-914
• /
• 2015

Reduction in the number of students due to the low birth rate has notice very many changes in the national education policies. The purpose of this study is to propose a method for estimation of the number of students (the population) by age or grade promotion rate of progression rate to estimate the exact number of students (the population) by 2032. It was suggested the nth moving average proportional method and the weighted proportional moving average method as the method of population projections. It presents the means and standard deviations of the measurement errors of the suggested methods by Monte Carlo simulation. Measured in this study are predicted result was a phenomenon is estimated lower than the actual value.