• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.380-383
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• 2003

In this paper, we propose a fuzzy group decision making method for multiple decision maker-multiple objective programming problems to obtain the agreeable solution. In the proposed method, considering the vague nature of human subjective judgement it is assumed that each of multiple decision makers has a fuzzy goal for each of his/her own objective functions. After eliciting the membership functions from the decision makers for their fuzzy goals, total M-Pareto optimal solution concept is defined in membership spaces in order to deal with multiple decision maker-multiple objective programming problems. For generating a candidate of the agreeable solution which is total M-Pareto optimal, the extended weighted minimax problem is formulated and solved for some weighting vector which is specified by the decision makers in their subjective manner, Given the total M-Pareto optimal solution, each of the derision makers must either be satisfied with the current values of the membership functions, or update his/her weighting vector, However, in general, it seems to be very difficult to find the agreeable solution with which all of the decision makers are satisfied perfectly because of the conflicts between their membership functions. In the proposed method, each of the decision makers is requested to estimate the degree of satisfaction for the candidate of the agreeable solution. Using the estimated values or satisfaction of each of the decision makers, the core concept is desnfied, which is a set of undominated candidates. The interactive algorithm is developed to obtain the agreeable solution which satisfies core conditions.

• Journal of the Korean Data and Information Science Society
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• 제16권3호
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• pp.549-556
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• 2005

A hard-type centroids in the conventional clustering algorithm such as k-modes algorithm cannot keep the uncertainty inherently in data sets as long as possible before actual clustering(decision) are made. Therefore, we propose the k-populations algorithm to extend clustering ability and to heed the data characteristics. This k-population algorithm as found to give markedly better clustering results through various experiments.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.865-868
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• 2000

In this paper we derive a new VAD algorithm, which combines the preprocessing algorithm and the optimum decision rule. To improve the performance of the VAD algorithm we employ the speech enhancement algorithm and then apply the maximal ratio combining technique in the preprocessing procedure, which leads to maximized output SNR. Moreover, we also perform extensive computer simulations to demonstrate the performance improvement of the proposed algorithm under various background noise environments.

• Smart Structures and Systems
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• 제20권1호
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• pp.99-114
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• 2017

In cognitive science, it is illustrated how the collective opinions of a group of individuals answers to questions involving quantity estimation. One example of this approach is introduced in this article as Star Graph (SG) algorithm. This graph describes the details of communication among individuals to share their information and make a new decision. A new labyrinthine network of neighbors is defined in the decision-making process of the algorithm. In order to prevent getting trapped in local optima, the neighboring networks are regenerated in each iteration of the algorithm. In this algorithm, the normal distribution is utilized for a group of agents with the best results (guidance group) to replace the existing infeasible solutions. Here, some new functions are introduced to provide a high convergence for the method. These functions not only increase the local and global search capabilities but also require less computational effort. Various benchmark functions and engineering problems are examined and the results are compared with those of some other algorithms to show the capability and performance of the presented method.

• 한국통신학회논문지
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• 제29권6A호
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• pp.660-666
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• 2004

OFDM (Othogonal Frequency Division Multiplexing) 시스템과 CDMA (Code Division Multiple Access) 시스템의 결합 방식인 OFDM-CDMA 시스템에서는 파일럿 심볼을 이용하여 얻어진 채널 추정값으로 데이터 신호를 보상할 수 있다. 일반적으로 파일럿 심볼의 상관관계를 이용한 MMSE (Minimum Mean-Squared Error) 추정기를 사용하면 최적의 채별 추정값을 얻어낼 수 있으나 구조가 복잡하다는 단점이 있다. 본 논문에서는 파일럿 심볼에 대한 정보만을 이용하는 간단한 구조의 PA (Pilot-Aided) 알고리즘과 파일럿 심볼과 데이터 심볼의 정보를 모두 이용하는 PADD (Pilot-Aided Decision-Directed) 알고리즘을 변형하여 기존의 채널추정 방법보다 간단한 구조를 가지는 새로운 알고리즘을 제안하구 컴퓨터 모의실험을 통해 레일레이 다중 경로 페이딩 환경에서 수신기의 속도를 변화시키면서 성능을 평가한다. 모의 실험 결과를 살펴보면 제안된 채널추정 알고리즘이 기존의 PA 알고리즘보다 성능이 우수함을 확인할 수 있다.

• Nuclear Engineering and Technology
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• 제44권7호
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• pp.755-766
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• 2012

A Binary Decision Diagram (BDD) is a graph-based data structure that calculates an exact top event probability (TEP). It has been a very difficult task to develop an efficient BDD algorithm that can solve a large problem since its memory consumption is very high. Recently, in order to solve a large reliability problem within limited computational resources, Jung presented an efficient method to maintain a small BDD size by a BDD truncation during a BDD calculation. In this paper, it is first identified that Jung's BDD truncation algorithm can be improved for a more practical use. Then, a more efficient truncation algorithm is proposed in this paper, which can generate truncated BDD with smaller size and approximate TEP with smaller truncation error. Empirical results showed this new algorithm uses slightly less running time and slightly more storage usage than Jung's algorithm. It was also found, that designing a truncation algorithm with ideal features for every possible fault tree is very difficult, if not impossible. The so-called ideal features of this paper would be that with the decrease of truncation limits, the size of truncated BDD converges to the size of exact BDD, but should never be larger than exact BDD.

• 방송공학회논문지
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• 제7권4호
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• pp.310-316
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• 2002

본 논문에서는 동영상 부호화 시 움직임 벡터의 고속 추정을 가능하게 하기 위한 적응 탐색 영역 결정 방식에 대해 제안한다. 시간적 과잉정보를 제거함으로써 압축 효율을 개선하고자 하는 움직임 벡터 추정을 위한 블록 매칭 방식 (BMA: Block Matching Algorithm)은 움직임 벡터의 정확성 및 계산량 측면에서 상호 교환적인 특성을 갖고 있다. 고속 움직임 추정을 위한 전처리 과정인 제안 방식은 인접 블록 움직임 벡터의 국부 통계 특성을 이용하여 움직임 탐색 영역을 적응적으로 결정한다. 실험 결과를 통해 제안된 방식이 압축 효율의 손상 없이 상당한 계산량이 줄었음을 확인할 수 있었다.

• 한국통신학회논문지
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• 제32권7C호
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• pp.635-643
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• 2007

본 논문에서는 OFDM(Orthogonal Frequency Division Multiplexing) 기반 셀룰라 시스템에서 채널추정 성능을 향상시키기 위한 DEM(Decision-directed Expectation Maximization) 알고리듬을 제안한다. DEM 알고리듬은 다중안테나를 사용하는 단말이 셀 경계지역에 위치하는 경우 데이터 신호를 이용하여 주파수 효율의 감소 없이 채널추정 성능을 향상시킬 수 있으며, 한 그룹 내 채널변화 성분을 고려하여 채널갱신을 함으로써 고속 이동환경에도 큰 열화 없이 채널추정 성능을 향상시킬 수 있다. 모의실험을 통하여 제안된 DEM 알고리듬이 EM(Expectation Maximization) 기법과 비교하여 고속이동 환경에서 채널추정 성능을 향상 시키면서 연산 복잡도를 크게 감소시킬 수 있음을 확인한다.

• 한국자기학회지
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• 제7권2호
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• pp.103-108
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• 1997

본 논문에서는 퍼지결정법을 적용한 유도전동기의 최적설계 방법을 제시하였다. 이 방법은 설계자의 경험, 관점, 판단을 반영할 수 있을 뿐만 아니라 다목적 최적설계에 쉽게 적용가능하다. 특성 해석방법은 등가 자기회로법이며, 설계방법은 기존 설계법 중의 하나인 D$^{2}$L 법에 퍼지 결정법과 최적화 루틴을 결합하였다. 사용한 최적화 알고리즘은 확률론적 최적화기법인 (1+1) Evolution Strategy(ES)를 이용하였다. 제안된 알고리즘은 유도전동기의 무게최소화와 동시에 주요 동작점에서의 효율, 역률을 최대화 설계하는 다중목적 최적설계에 적용되었다.

• 전기학회논문지
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• 제56권7호
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• pp.1183-1190
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• 2007

This paper proposes the improved fault decision algorithm using DWT(Discrete Wavelet Transform) and ANNs for the FRTU(Feeder Remote Terminal Unit) on the feeder in the power distribution system. Generally, the FRTU has the fault decision scheme detecting the phase fault, the ground fault. Especially FRTU has the function for 2000ms. This function doesn't operate FI(Fault Indicator) for the Inrush current generated in switching time. But it has a defect making it impossible for the FI to be operated from the real fault current in inrush restraint time. In such a case, we can not find the fault zone from FI information. Accordingly, the improved fault recognition algorithm is needed to solve this problem. The DWT analysis gives the frequency and time-scale information. The neural network system as a fault recognition was trained to distinguish the inrush current from the fault status by a gradient descent method. In this paper, fault recognition algorithm is improved by using voltage monitoring system, DWT and neural network. All of the data were measured in actual 22.9kV power distribution system.