• 한국지능시스템학회논문지
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• 제13권5호
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• pp.512-519
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• 2003

본 논문에서는 계층적 클러스터링과 GMM을 순차적으로 이용하여 최적의 파라미터를 추정하고 이를 뉴로-퍼지 모델의 초기 파리미터로 사용하여 모델의 성능 개선을 제안한다. 반복적인 시도 중 가장 좋은 파라미터를 선택하는 기존의 알고리즘 과 달리 계층적 클러스터링은 데이터들 간의 유클리디언 거리를 이용하여 클러스터를 생성하므로 반복적인 시도가 불필요하다. 또한 클러스터링 방법에 의해 퍼지 모델링을 행하므로 클러스터와 동일한 갯수의 적은 규칙을 갖는다. 제안된 방법의 유용함을 비선형 데이터인 Box-Jenkins의 가스로 예측 문제와 Sugeno의 비선형 시스템에 적용하여 이전의 연구보다 적은 규칙으로도 성능이 개선되는 것을 보였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.110.1-110
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• 2002

We propose a novel neuro-fuzzy system based on an efficient clustering method. It is a very useful method that improves the performance of a fuzzy model with small number of fuzzy rules. The fuzzy clustering methods are studied in the wide range of fuzzy modeling. One of them, the grid partition method has problem of exponentially increasing number of rules when the dimension of input or number of membership function is linearly increased. On the other hand, the Expectation Maximization algorithm is an efficient estimation for unknown parameters of the Gaussian mixture model. Here it is noted that the parameters can be used for fuzzy clustering method. In a fuzzy modeling, it is desired that...

• 조명전기설비학회논문지
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• 제16권5호
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• pp.104-111
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• 2002

본 논문에서는 EM(Expectation-Maximization) 알고리즘을 이용한 자동적인 퍼지 규칙생성과 적응 뉴로-퍼지 제어기(Adaptive Neuro-Fuzzy Controller)의 설계를 제안한다. EM 알고리즘은 가우시안 혼합모델(Gaussian Mixture Model)의 최대우도추정(Maximum Likelihood Estimate)을 위해 사용되어지며 본 논문에서는 규칙생성을 위해 클러스터 중심을 추정한다. 추정된 클러스터는 ANFIS(Adaptive Neuro-Fuzzy Inference System)의 퍼지 규칙과 소속함수를 구축하는데 사용되어진다. 시뮬레이션으로 제안된 적응 뉴로-퍼지 제어기의 성능을 입증하기 위해 목욕물 온도 제어 시스템에 대해 다루고 기존 퍼지 제어기에 비해 적은 규칙의 수와 작은 값의 SAE(Sum of Absolute Error)으로 성능개선을 확인하였다.

• Geomechanics and Engineering
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• 제3권4호
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• pp.267-284
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• 2011

The aim of the paper is to study the hydro-mechanical behaviour of a tuff and calcareous sand mixture. A first experimental phase was carried out in order to find the optimal mixture. This showed that the material composed of 80% tuff and 20% calcareous sand provides the maximum mechanical strength. The second experimental phase concerns the study of the drying- wetting behaviour of the optimal mixture. Triaxial shear tests in saturated and unsaturated states at constant water content were carried out on samples initially compacted at the MPO. Experimental results let to deduce the parameters necessary for the prediction of the hydro-mechanical behaviour of pavement formulated from tuff and calcareous sand mixtures, related to moisture. This optimal mixture satisfies the regulation rules and hence constitutes a good local eco-material, abundantly available, for the conception of pavements.

• 대한음성학회:학술대회논문집
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• 대한음성학회 2006년도 추계학술대회 발표논문집
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• pp.80-83
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• 2006

The purpose of this paper is to build a pronunciation lexicon with estimated likelihoods of the phonetic rules based on the phonetic realizations and therefore to improve the performance of CSR using the dictionary. In the baseline system, the phonetic rules and their application probabilities are defined with the knowledge of Korean phonology and experimental tuning. The advantage of this approach is to implement the phonetic rules easily and to get stable results on general domains. However, a possible drawback of this method is that it is hard to reflect characteristics of the phonetic realizations on a specific domain. In order to make the system reflect phonetic realizations, the likelihood of phonetic rules is reestimated based on the statistics of the realized phonemes using a forced-alignment method. In our experiment, we generates new lexica which include pronunciation variants created by reestimated phonetic rules and its performance is tested with 12 Gaussian mixture HMMs and back-off bigrams. The proposed method reduced the WER by 0.42%.

• 호남수학학술지
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• 제25권1호
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• pp.95-115
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• 2003

Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}(p{\geq}4)$ under the quadratic loss, based on a sample $X_1,\;{\cdots}X_n$. We find an optimal decision rule within the class of Lindley type decision rules which shrink the usual one toward the mean of observations when the underlying distribution is that of a variance mixture of normals and when the norm $||{\theta}-{\bar{\theta}}1||$ is known, where ${\bar{\theta}}=(1/p)\sum_{i=1}^p{\theta}_i$ and 1 is the column vector of ones. When the norm is restricted to a known interval, typically no optimal Lindley type rule exists but we characterize a minimal complete class within the class of Lindley type decision rules. We also characterize the subclass of Lindley type decision rules that dominate the sample mean.

• 통합자연과학논문집
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• 제5권3호
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• pp.186-189
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• 2012

For the mean vector of a p-variate normal distribution ($p{\geq}3$), the optimal estimation within the class of James-Stein type decision rules under the quadratic loss are given when the underlying distribution is that of a variance mixture of normals and when the norm ${\parallel}\underline{{\theta}}{\parallel}$ in known. It also demonstrated that the optimal estimation within the class of Lindley type decision rules under the same loss when the underlying distribution is the previous type and the norm ${\parallel}{\theta}-\overline{\theta}\underline{1}{\parallel}$ with $\overline{\theta}=\frac{1}{p}\sum\limits_{i=1}^{n}{\theta}_i$ and $\underline{1}=(1,{\cdots},1)^{\prime}$ is known.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2004년도 추계학술발표대회 논문집
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• pp.175-179
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• 2004

Since the electromagnetic properties of fiber reinforced polymeric composites can be tailored effectively by adding small amount of electromagnetic powders to the matrix of composites, they are plausible materials for fabricating the radar absorbing structures (RAS) of desired performance. In order to design the effective electromagnetic wave (EM) absorber with the fiber reinforced polymeric composites, the electromagnetic characteristics with respect to the constituents of the composite should be available in the target frequency band. In order to describe the dielectric behavior of low loss unidirectional fiber reinforced composite, theoretical models and mixture equations for estimating its dielectric constant were proposed with respect to the fiber, matrix volume fractions and fiber orientations, and verified by the experiments. From the investigation, it was found that the suggested binary mixture rules agreed well with the experimental results.

• Geomechanics and Engineering
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• 제2권3호
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• pp.213-227
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• 2010

Compacted layers of sand-bentonite mixtures have been proposed and used in a variety of geotechnical projects as engineered barriers for the enhancement of impervious landfill liners, cores of zoned earth dams and radioactive waste repository systems. This paper presents a study on the valorization of local materiel such as dune sand from Laghouat region and mine bentonite intended for the realization of liner base layers in the conception of insulation barriers for hazardous waste centers. In the practice we try to get an economical mixture that satisfies the hydraulic and mechanical properties specified by regulation rules. The effect of the bentonite additions on the mixture is reflected by its capability of clogging the matrix pores upon swelling. In order to get an adequate dune sand-bentonite mixture, an investigation on hydraulic and mechanical behaviours is carried out in this study for different mixtures. Using oedometer test, the adequate bentonite addition to the mixture, which satisfies the conditions on permeability, is found to be around 12% to 15%. These results are also confirmed by direct measurement using triaxial cell.

• Journal of the Korean Data and Information Science Society
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• 제16권4호
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• pp.1027-1039
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• 2005

Consider the problem of estimating a $p{\times}1$ mean vector $\theta(p\geq4)$ under the quadratic loss, based on a sample $X_1$, $X_2$, $\cdots$, $X_n$. We find a Lindley type decision rule which shrinks the usual one toward the mean of observations when the underlying distribution is that of a variance mixture of normals and when the norm $\parallel\;{\theta}-\bar{{\theta}}1\;{\parallel}$ is restricted to a known interval, where $bar{{\theta}}=\frac{1}{p}\;\sum\limits_{i=1}^{p}{\theta}_i$ and 1 is the column vector of ones. In this case, we characterize a minimal complete class within the class of Lindley type decision rules. We also characterize the subclass of Lindley type decision rules that dominate the sample mean.