• 경영과학
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• 제18권1호
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• pp.135-145
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• 2001

In recent environment of dynamic management, there is growing recognition that information and knowledge management systems are essential for efficient/effective decision making by CEO. To cope with this situation, we suggest the Data-Miming scheme as a key component of integrated information and knowledge management system. The proposed system measures business performance by considering both VA(Value-Added), which represents stakeholder’s point of view and EVA (Economic Value-Added), which represents shareholder’s point of view. To mine the new information & Knowledge discovery, we applied the improved genetic algorithms that consider predictability, understandability (lucidity) and reasonability factors simultaneously, we use a linear combination model for GAs learning structure. Although this model’s predictability will be more decreased than non-linear model, this model can increase the knowledge’s understandability that is meaning of induced values. Moreover, we introduce a random variable scheme based on normal distribution for initial chromosomes in GAs, so we can expect to increase the knowledge’s reasonability that is degree of expert’s acceptability. the random variable scheme based on normal distribution uses statistical correlation/determination coefficient that is calculated with training data. To demonstrate the performance of the system, we conducted a case study using financial data of Korean automobile industry over 16 years from 1981 to 1996, which is taken from database of KISFAS (Korea Investors Services Financial Analysis System).

• 전기학회논문지
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• 제66권4호
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• pp.692-700
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• 2017

In this paper, we propose the structural design of Interval Type-2 FCM based RBFNN. Proposed model consists of three modules such as condition, conclusion and inference parts. In the condition part, Interval Type-2 FCM clustering which is extended from FCM clustering is used. In the conclusion part, the parameter coefficients of the consequence part are estimated through LSE(Least Square Estimation) and WLSE(Weighted Least Square Estimation). In the inference part, final model outputs are acquired by fuzzy inference method from linear combination of both polynomial and activation level obtained through Interval Type-2 FCM and acquired activation level through Interval Type-2 FCM. Additionally, The several parameters for the proposed model are identified by using differential evolution. Final model outputs obtained through benchmark data are shown and also compared with other already studied models' performance. The proposed algorithm is performed by using Iris and Vehicle data for pattern classification. For the validation of regression problem modeling performance, modeling experiments are carried out by using MPG and Boston Housing data.

• International journal of advanced smart convergence
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• 제8권2호
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• pp.155-161
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• 2019

We introduces a mobile robot that can navigate on a power transmission line arranged in bundled conductors. The designs of the proposed robot are performed for navigation on bundled conductors, and the navigation method for bundled conductors and obstacle avoidance are presented. The robot consists of 13 degrees of freedom (DOF) with a symmetrical structure for the left and right parts, including the four wheel joints. The navigation method is designed using a combination of three motion primitives such as linear motion of counterbalancing box, linear motion of robot arm, and rotational motion of wheel part. To examine the performance of the proposed robot, navigation simulations are conducted using $ADAMS^{TM}$. The robot navigations were simulated on obstacle environments that consisted of two- and four-conductor bundles. Based on the simulation results, the performance of the proposed robot was reviewed through the analysis of the trajectories of end-effectors. We confirmed that the proposed robot was capable of achieving optimal navigation on bundled conductors that included obstacles.

• Environmental Engineering Research
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• 제24권2호
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• pp.220-237
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• 2019

Solid waste management (SWM) is one of the poorly rendered services in developing countries - limited resources, increasing population, rapid urbanization and application of outdated systems leads to inefficiency. Lack of proper planning and inadequate data regarding solid waste generation and collection compound the SWM problem. Decision makers need to formulate solutions that consider multiple goals and strategies. Given the large number of available options for SWM and the inter-relationships among these options, identifying SWM strategies that satisfy economic or environmental objectives is a complex task. The paper develops a mathematical model for a municipal Integrated SWM system, taking into account waste generation rates, composition, transportation modes, processing techniques, revenues from waste processing, simulating waste management as closely as possible. The constraints include those linking waste flows and mass balance, processing plants capacity, landfill capacity, transport vehicle capacity and number of trips. The linear programming model integrating different functional elements was solved by LINGO optimization software and various possible waste management options were considered during analysis. The model thus serves as decision support tool to evaluate various waste management alternatives and obtain the least-cost combination of technologies for handling, treatment and disposal of solid waste.

• 한국농공학회지
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• 제22권3호
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• 한국전산구조공학회논문집
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• 제32권2호
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• pp.117-124
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• 2019

대규모 유한요소 모델을 빠르게 해석하기는 위해서 병렬 희소 솔버를 필수적으로 적용해야 한다. 이 논문에서는 미세하게 변화하는 시스템 행렬을 대상으로 연속적으로 해를 구해야 하는 문제에서 효율적으로 적용가능한 반복-직접 희소 솔버 조합 기법을 소개한다. 반복-직접 희소 솔버 조합 기법은 병렬 희소 솔버 패키지인 PARDISO에 제안 및 구현된 기법으로 새롭게 행렬값이 갱신된 선형 시스템의 해를 구할 때 이전 선형 시스템에 적용된 직접 희소 솔버의 행렬 분해(factorization) 결과를 Krylov 반복 희소 솔버의 preconditioner로 활용하는 방법을 의미한다. PARDISO에서는 미리 설정된 반복 회수까지 해가 수렴하지 않으면 직접 희소 솔버로 해를 구하며, 이후 이어지는 갱신된 선형 시스템의 해를 구할 때는 최종적으로 사용된 직법 희소 솔버의 행렬 분해 결과를 preconditioner로 사용한다. 이 연구에서는 첫 번째 Krylov 반복 단계에서 소요되는 시간을 동적으로 계산하여 최대 반복 회수를 설정하는 기법을 제안하였으며, 주파수 영역 해석에 적용하여 그 효과를 검증하였다.

• 한국정보통신학회논문지
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• 제19권12호
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• pp.2792-2799
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• 2015

본 논문에서는 화자 인식의 성능을 개선하기 위해서 glottal flow로부터 source mel-frequency cepstral coefficient (SMFCC), 왜도, 첨도를 추출하여 활용하였다. 일반적으로 glottal flow의 고주파 대역은 응답의 크기가 평탄하므로 미리 정한 차단주파수 미만에 대해서만 SMFCC를 추출한다. 추출된 SMFCC, 왜도, 첨도는 종래의 특징 파라미터와 결합된 후 종래의 화자인식 시스템과 동등한 조건에서의 성능 비교를 위하여 principal component analysis (PCA) 및 linear discriminiat analysis (LDA)를 통한 차원축소가 행해진다. 대용량의 화자인식 실험결과를 통해서 제안된 인식 시스템이 종래의 화자인식 시스템 보다 더 좋은 성능을 나타냄을 확인할 수 있었으며, 특히 가우시안 혼합이 낮을 때 더 높은 성능향상을 나타내었다.

• 한국측량학회지
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• 제7권2호
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• pp.85-92
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• 1989

본 연구에서는 원격탐사 기법을 이용하여 인공위성 MSS 데이타와 TM 데이타를 몇 가지의 선형변환된 데이타로 변형시킴으로 분류 정확도향상과 특정 대상물에서의 유효 변환데이타 조합을 알아내고자 하는 것이 주된 목적이라 하겠다. LANDSAT 데이타를 처리함에 있어서, 문제점 중의 하나가 자료의 방대함이며, 이 방대한 자료에 대하여 보다 효율적이고 경제적인 분석을 행하기 위한 방법이 선형변환이다. 이 방법은 여러가지 선형적 산술과 통계적 변환을 하여 다파장 데이타들을 변환시킴으로써, (1) 복잡한 데이타에 대해서는 단순함을 제공 (2) 중복 데이타에 대한 선택적 처리 및 불필요한 자료 제거 (3) 연구대상에 대한 강조등을 행한다. 본 연구에서는 Band Ratioing과 PCA를 수행하여 자료를 변환 분석하여 보았다. 분류 결과 Infrared/RED Ratio는 식물의 특성을 확장시켜 다른 분류 항목과 구별하여 분류하는 데 유용하였으며, 주성분 분석 결과 녹색식물역의 분류에 있어서 Band 1,27이 효과적이었다.

• 스마트미디어저널
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• 제10권3호
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• pp.23-30
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• 2021

제조 시계열 데이터 클러스터링 기법은 제조 대용량 데이터 기반 군집화를 통한 설비 및 공정 이상 탐지 분류를 위한 중요한 솔루션이지만 기존 정적 데이터 대상 클러스터링 기법을 시계열 데이터에 적용함에 있어 낮은 정확도를 가지는 단점이 있다. 본 논문에서는 진화 연산 기반 시계열 군집 분석 접근 방식을 제시하여 기존 클러스터링 기술에 대한 정합성 향상하고자 한다. 이를 위하여 먼저 제조 공정 결과 이미지 형상을 선형 스캐닝을 활용하여 1차원 시계열 데이터로 변환하고 해당 변환 데이터 대상으로 Pearson 거리 매트릭을 기반으로 계층적 군집 분석 및 분할 군집 분석에 대한 최적 하위클러스터를 도출한다. 해당 최적 하위클러스터 대상 유전 알고리즘을 활용하여 유사도가 최소화되는 최적의 군집 조합을 도출한다. 그리고 실제 제조 과정 이미지 대상으로 기존 클러스터링 기법과 성능 비교를 통하여 제안된 클러스터링 기법의 성능 우수성을 검증한다.

• 국제강구조저널
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• 제18권5호
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• pp.1617-1630
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• 2018

The crucial differences between conventional rail with split-type connectors and continuous welded rails are axial stress in the longitudinal direction and stability, as well as other issues generated under the influence of loading effects. Longitudinal stresses generated in continuously welded rails on railway bridges are strongly influenced by the nonlinear behavior of the supporting system comprising sleepers and ballasts. Thus, the track structure interaction cannot be neglected. The rail-support system mentioned above has properties of non-uniform material distribution and uncertainty of construction quality. The linear elastic hypothesis therefore cannot correctly evaluate the stress distribution within the rails. The aim of this study is to apply the nonlinear finite element method using the nonlinear coupling interface between the track and structural model and to illustrate the welded rail behavior under the loading effect and uncertain factors of the ballast. Numerical results of nonlinear finite analysis with a three-dimensional solid and frame element model are presented for a typical track-bridge system. A composite plate girder, modeled by solid and shell elements, is also analyzed to consider the behavior of the welded rail. The analysis result showed buckling under the independent calculations of load cases, including 'temperature change', 'bending of the supporting structure', and 'braking' of the railway vehicle. A parametric study of the load combination method and the loading sequence is also included in this analysis.