• Communications for Statistical Applications and Methods
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• v.24 no.1
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• pp.67-80
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• 2017

Over the last few decades, ensemble forecasts based on global climate models have become an important part of climate forecast due to the ability to reduce uncertainty in prediction. Moreover in ensemble forecast, assessing the prediction uncertainty is as important as estimating the optimal weights, and this is achieved through a probabilistic forecast which is based on the predictive distribution of future climate. The Bayesian model averaging has received much attention as a tool of probabilistic forecasting due to its simplicity and superior prediction. In this paper, we propose a new Bayesian model averaging method for probabilistic ensemble forecasting. The proposed method combines a deterministic ensemble forecast based on a multivariate regression approach with Bayesian model averaging. We demonstrate that the proposed method is better in prediction than the standard Bayesian model averaging approach by analyzing monthly average precipitations and temperatures for ten cities in Korea.

• Journal of Korea Water Resources Association
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• v.33 no.S1
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• pp.37-47
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• 2000

The method of delays is widely used for reconstruction chaotic attractors from experimental observations. Many studies have used a fixed delay time ${\tau}_d$ as the embedding dimension m is increased, but this is not necessarily the best choice for obtaining good convergence of the correlation dimension. Recently, some researchers have suggested that it is better to fix the delay time window ${\tau}_w$ instead. Unfortunately, ${\tau}_w$ cannot be estimated using either the autocorrelation function or the mutual information, and no standard procedure for estimating ${\tau}_w$ has yet emerged. However, a new technique, called the C-C method, can be used to estimate either ${\tau}_d\;or\;{\tau}_w$. Using this method, we show that, for small data sets, fixing ${\tau}_w$, rather than ${\tau}_d$, does indeed lead to a more rapid convergence of the correlation dimension as the embedding dimension m in increased.

• Advances in Traditional Medicine
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• v.10 no.2
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• pp.79-85
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• 2010

The methanolic extract of natural roots of Mucuna pruriens was screened for hepatoprotective and antioxidant effects in carbon tetrachloride ($CCl_4$) induced hepatotoxicity in Albino rats. The degree of protection was measured by estimating biochemical parameters like serum glutamate oxaloacetate transaminase, serum glutamate pyruvate transaminase, total protein and level of serum bilirubin (both total and direct). The extract also reduced $CCl_4$ induced lipid peroxidation both in-vitro and in-vivo. Hepatoprotective activity of methanolic extract at dose 300 mg/kg body weight, i.p., was comparable with standard drug Silymarin (25 mg/kg, i.p.). Furthermore, histopathological experiments were also carried out to support the study.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.41 no.1
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• pp.54-60
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• 2008

High- and multi-frequency acoustic systems can measure a zooplankton patch successively and estimate the spatial distribution and abundance of zooplankton according to size using a multi-frequency inversion (MFI) method. This study measured zooplankton distribution to a depth of 150m using a multi-frequency acoustic system (TAPS-6), installed on a CTD system with a fluorometer and analyzed it using the MFI method. Simultaneously, zooplankton samples were collected by north pacific standard (NORPAC) net to confirm the species composition. The results showed that the combined method is valuable for estimating the zooplankton profile in detail and investigating the relationship between the zooplankton and phytoplankton profiles.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.370-370
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• 2000

In this paper, we design a Multi-Fuzzy model by means of HCM clustering and genetic algorithms for a nonlinear system. In order to determine structure of the proposed Multi-Fuzzy model, HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy ate identified by genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy mode] and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.181-186
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• 2005

Many data sets obtained from surveys or medical trials often include missing observations. When these data sets are analyzed, it is general to use only complete cases. However, it is possible to have big biases or involve inefficiency. In this paper, we consider a method for estimating parameters in logistic linear models involving non-ignorable missing data mechanism. A binomial response and normal exploratory model for the missing data are used. We fit the model using the EM algorithm. The E-step is derived by Metropolis-hastings algorithm to generate a sample for missing data and Monte-carlo technique, and the M-step is by Newton-Raphson to maximize likelihood function. Asymptotic variances of the MLE's are derived and the standard error and estimates of parameters are compared.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.8
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• pp.130-137
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• 1999

The criteria for determining the elements are the minimum zone method(MZM) and the least squares method(LSM). The LSM is deterministic and simple but is limited at the measurements whose errors are significant compared with form errors. For the precise condition, minimum zone method(MZM) has been selected to determine the elements. It is not deterministic and nonlinear so that a optimizing procedure is needed. The Straightness is the fundamental problem in the evaluating form error. In this paper, a new approach adapting the genius education concept is proposed to obtain an accurate results for the minimum zone problem of the straightness. Its computational algorithm is studied on a set of randomly generated data. To be of almost no account of the specification(the number and the standard devistion etc.) of the sample data, the results shows excellent reliability and high accuracy in estimating the straightness.

• Transactions of the Korean Society of Mechanical Engineers
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• v.10 no.5
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• pp.601-610
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• 1986

The acoustic intensity in the very near field of a vibrating surface reveals information about the location of sound sources and sinks. A system model of tennis racket was developed from simultaneous measurement of excitation force, surface vibration and the near field sound pressure. The characteristics of structural dynamics were obtained by standard experimental modal analysis techniques while the sound radiation characteristics were determined by estimating the acoustic intensity. In this paper, the information about vibration behviour was obtained by acoustic intensity method and some, experiments for verification were carried out. Close correlation was found between experimentally determined acoustic intensity and vibration mode patterns of the tennis racket.

• Journal of Korean Society for Quality Management
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• v.4 no.1
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• pp.20-24
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• 1976

The higher develops the industrial techniques, the more reliability of mac hi nary, equipments and systems want the consumers. So, it is a key to succeed in the new-product development that the consumers can put reliance on the product to be made in the product design stage. This study intends to help the product designer and the system manager by presenting them better reliability prediction techniques. For this purpose, the author built some fundamental reliability system models. And then predict the system reliability by estimating the elemental component's failure rate ${\lambda}_i$, and proposed an evaluation model. And also, a system is wrong according to the component's characteristics' degradation, we must estimate the degradation failure rate (average and standard deviation). For this, the "Moment method" is used.

• Journal of Electrical Engineering and information Science
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• v.2 no.4
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• pp.72-78
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• 1997

A free space transmission method using standard gain horn antennas in the frequency range from 9.0 to 10.5GHz is applied to determine the dielectric properties of grain such as rough rice ,brown rice and barley. The dielectric constant and loss factor, which depend on the moisture content of the wetted grain are obtained from the measured attenuation and phase shift by vector network analyzer. The moisture content of grain varied from 11 to 25% based on this wetted condition. The measured values of dielectric constants as a function of moisture density are compared with values of those obtained using he predicted model for estimating dielectric constants of grain. The effect of density fluctuation, high is an important parameter governing the dielectric properties of grain, on the dielectric constant and loss factor is presented. A new density-independent model in terms of measured attenuation an moisture density is proposed of reducing the effects of density fluctuation on the moisture content measurement.