• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.92-100
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• 1999

In the microcell mobile communication, we propose algorithms processing operational disposition to exactly analysis propagation environments from the base station to mobile stations. Algorithms are developed by the triangle analysis method can operate variable propagation paths and reflect numbers. For simulation, we suppose that mobile stations are located in the shadow region of the line of sight and the area of the non-line of sight sloping against the line of sight area at variable angles. By analyzing the results of simulation using proposed algorithms, we can be applied to the optimal position selection of the base station in the microcell mobile communication.

• Journal of Korea Water Resources Association
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• v.32 no.3
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• pp.247-254
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• 1999

The frequency analyses of annual maximum rainfall data for 22 rainfall gauging stations is Korea were performed. The method of moments (MOM), maximum likelihood (ML), and probability weighted moments (PWM) were used in parameter estimation. The GEV distribution was selected as an appropriate model for annual maximum rainfall data based on parameter validity condition, graphical analysis, separation effect, and goodness of fit tests. For the selected GEV model, spatial analysis was performed and rainfall intensity-duration-frequency equation was derived by using linearization technique. The derived rainfall intensity-duration-frequency equation can be used for estimating rainfall quantiles of the selected stations with convenience and reliability in practice.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.77-80
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• 2003

신경망의 퍼셉트론 학습법에는 이진 또는 연속 활성화 함수가 사용된다. 초기 연결강도는 임의의 값으로 설정하며, 목표치와 실제 출력과의 차이를 이용하는 것이 주된 특징이다. 즉 구해진 오차는 학습률에 따라서 다음 단계의 연결강도에 영향을 주게 된다. 이런 경우 학습률이 너무 크면 수렴성을 보장할 수 없으며, 반대로 너무 작게 선정하면 학습이 매우 느리게 진행되는 단점이 발생한다. 이런 이유로 능동적인 학습률의 변화는 신경망의 퍼셉트론 학습법에 중요한 관건이 리며, 주어진 문제를 최적으로 학습을 위해서는 결국 상황에 따른 적절한 학습률 조정이 필요하다. 본 논문에서는 학습률 조정에 퍼지 모델을 적용하는 신경망 학습 방법을 제안하고자 한다. 제안한 방법에 의한 학습은 오차의 변화에 따라 학습률을 조정하는 방식을 사용하였고, 그 결과 연결강도를 능동적으로 변화시켜 효과적인 학습 결과를 얻었다. 학습률 변화는 'Sugeno 퍼지 모델'을 이용하여 구현하였다.

• Journal of the Korean Institute of Gas
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• v.10 no.4 s.33
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• pp.52-62
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• 2006

In this study, we tried to propose a selection method of release scenarios and a method of consequence analysis at a gas explosion by pipe release. Thus, release rates, damage areas of the facilities, and fatality areas were estimated and analyzed at various release conditions(temperature, pressure, release material, etc). As a results, we could conclude that the rupture was the worst case of release scenarios, and at release rates and damage areas were better estimated by the weighted average method considering a generic failure frequency of the release hole than by an arbitrary selection of the release hole.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.20 no.1
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• pp.57-63
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• 2007

The systematic method to construct equivalent static load from a given dynamic load is proposed in the present study. Previously reported works to construct equivalent static load were based on ad hoc methods. Due to improper selection of loading position, they may results in unreliable structural design. The present study proposes the employment of primary degrees of freedom for imposing the equivalent static loads. The degrees of freedom are selected by two-level condensation scheme with reliability and efficiency. In several numerical examples, the efficiency and reliability of the proposed scheme is verified by comparison displacement for equivalent static loading and dynamic loading at the critical time.

• Journal of the Korean Ceramic Society
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• v.33 no.12
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• pp.1325-1330
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• 1996

A new numerical method for determining the surface tension of a liquid drop by experimental measurement of the contour of the sessile drop is explained. in the present method a very simple and short computer program enables the calculation of surface tension in a few seconds even by a low speed personal computer. It need not the use of any other numerical tables or complex techniques. X and Z-corrdinates at one point on the contour of a sessile drop and the tangential angle at that point are all the data needed when the density of the drop is known. The results were compared with the values derived by a conventional method. This method can be used for the confirmation of measuring accuracy. Also the same concepts can be applied for the pendant drop method by changing only the sign of Z-coordinate from "+" to "-"ot; to "-"ot;-"quot.

• Explosives and Blasting
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• v.37 no.2
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• pp.14-21
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• 2019

Distinct element method is a powerful numerical tool for modelling the jointed rock masses. It is also a useful tool for modelling of later stage of blasting requiring large displacement. The distinct element method utilizes a rigid block idea in which the interacting force between distinct elements is calculated from contact displacement as elements penetrate slightly. The properties of joints defined as the boundaries of distinct elements are critical parameters to determine the block behavior, and affect the deformation and failure mode. However, regardless of real joint properties, joint stiffnesses have sometimes been selected without special concern just to prevent elements from penetrating too far into each other in some quasi-static problems. Depending on whether the main interest in the analysis is the prediction of the deformation with high precision, or the prediction of the block behaviour after failure, the input data such as joint stiffness may or may not have a significant effect on the results. The purpose of this study is to provide a sound understanding of the effect of the joint stiffness on the distinct element analysis results, and to help guide the selection of input data.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.516-524
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• 2004

In this paper, the initial value problem in clustering using K-means or Fuzzy-c-means is considered to reduce the number of iterations. Conventionally the initial values in clustering using K-means or Fuzzy-c-means are chosen randomly, which sometimes brings the results that the process of clustering converges to undesired center points. The choice of intial value has been one of the well-known subjects to be solved. The system of clustering using K-means or Fuzzy-c-means is sensitive to the choice of intial values. As an approach to the problem, the uniform partitioning method is employed to extract the optimal initial point for each clustering of data. Experimental results are presented to demonstrate the superiority of the proposed method, which reduces the number of iterations for the central points of clustering groups.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.859-868
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• 2004

We propose a method of selecting initial training examples for active learning so that it can reach high accuracy faster with fewer further queries. Our method is based on the assumption that an active learner can reach higher performance when given an initial training set consisting of diverse and typical examples rather than similar and special ones. To obtain a good initial training set, we first cluster examples by using k-means clustering algorithm to find groups of similar examples. Then, a representative example, which is the closest example to the cluster's centroid, is selected from each cluster. After these representative examples are labeled by querying to the user for their categories, they can be used as initial training examples. We also suggest a method of using the centroids as initial training examples by labeling them with categories of corresponding representative examples. Experiments with various text data sets have shown that the active learner starting from the initial training set selected by our method reaches higher accuracy faster than that starting from randomly generated initial training set.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.11 no.1
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• pp.34-36
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• 1997

In this paper, we introduce the design method using CAE(Computer Aided Engineering) which is profitable in the compatibility and standardization of the developed product and the reduction of construction time and price to develop and design a machine equipment. Particularly, we select the standard model to design or develop from the large machinery to the super precision one, extract the peculiar characters of the model by the close analysis of the physical and technical part, can predict the previous result of experimental characteristics on objective dimensions through the analogical mathematical analysis, and can induce the design model demanded by user investigating optimal data in advance. We present the analogical algorithms and process method of design factors and restriction factors in the systematization design with computer. Then we analyze step functions for each systematization equipment and induce the process of technical data with actuator model.