• Journal of the Institute of Convergence Signal Processing
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• v.14 no.3
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• pp.169-180
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• 2013

The modification of conditional Fuzzy C-Means (CFCM) with Gaussian weights (CFCM_GW) is accomplished for blind equalization of channels in this paper. The proposed CFCM_GW can deal with both of linear and nonlinear channels, because it searches for the optimal desired states of an unknown channel in a direct manner, which is not dependent on the type of channel structure. In the search procedure of CFCM_GW, the Bayesian likelihood fitness function, the Gaussian weighted partition matrix and the conditional constraint are exploited. Especially, in contrast to the common Euclidean distance in conventional Fuzzy C-Means(FCM), the Gaussian weighted partition matrix and the conditional constraint in the proposed CFCM_GW make it more robust to the heavy noise communication environment. The selected channel states by CFCM_GW are always close to the optimal set of a channel even when the additive white Gaussian noise (AWGN) is heavily corrupted. These given channel states are utilized as the input of the Bayesian equalizer to reconstruct transmitted symbols. The simulation studies demonstrate that the performance of the proposed method is relatively superior to those of the existing conventional FCM based approaches in terms of accuracy and speed.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.11
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• pp.1429-1436
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• 2011

In this paper, a new tube-radius-measuring algorithm has been proposed for effectively measuring the radii of small tubes under severe noise conditions that can also perform well when metal scraps that make it difficult to measure the radius correctly are inside the tube hole. In the algorithm, we adopt a fuzzy searching method that searches for the center of the inner circle by using fuzzy parameters for distance and orientation from the initial search point. The proposed algorithm has been implemented and tested on both synthetic and real-world tube images, and the performance is compared to existing circle-detection algorithms, such as the Hough transform and RANSAC methods, to prove the accuracy and effectiveness of the algorithm. From this comparison, it is concluded that the proposed algorithm has excellent performance in terms of measurement accuracy and computation time.

• Korean Business Review
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• v.15
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• pp.99-114
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• 2002

Recently several business models concerning e-Business has been introduced. But the different environment for each business requires the business model which is contingent to its specific situation. We, therefore, need to develop the e-Business models considering environment factors such as capital size, technology level, collection ability and amount of information, profit or target customers, etc. There can be several ways to create the value of an e-Business firm. A way among them is to develop limited area by focusing on core parts of the firm. This way leads for the firm to search the investment priority in order to solve the problem, which is to set a proper production and investment level for concentrating on competitively excellent areas of the firm. In this paper, we propose a method to decide the investment priority effectively when making a decision using fuzzy information. The method by our model is to minimize tolerances of given business fuzzy goals.

• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.306-316
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• 2013

The semiconductor industry has grown rapidly, and subsequently production planning problems have raised many important research issues. The reentrant flow-shop (RFS) scheduling problem with time windows constraint for harddisk devices (HDD) manufacturing is one such problem of the expanded semiconductor industry. The RFS scheduling problem with the objective of minimizing the makespan of jobs is considered. Meeting this objective is directly related to maximizing the system throughput which is the most important of HDD industry requirements. Moreover, most manufacturing systems have to handle the quality of semiconductor material. The time windows constraint in the manufacturing system must then be considered. In this paper, we propose a hybrid genetic algorithm (HGA) for improving chromosomes/offspring by checking and repairing time window constraint and improving offspring by left-shift routines as a local search algorithm to solve effectively the RFS scheduling problem with time windows constraint. Numerical experiments on several problems show that the proposed HGA approach has higher search capability to improve quality of solutions.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.215-218
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• 2011

본 논문에서는 비파괴 검사를 이용하여 획득한 세라믹 소재 영상에서 효율적으로 결함을 검출하는 방법을 제안한다. 제안된 방법은 세라믹 소재 영상에 비등방성 필터링 기법과 가우시안 필터링 기법을 반복 적용하여 잡음을 제거하고, Ends-in Search Stretching 기법을 적용하여 명암 대비를 강조한다. 명암 대비가 강조된 영상에 $7{\times}7$ Sobel 마스크를 적용하여 윤곽선을 추출한 후, 임계치 이진화 기법을 적용하여 영역을 세분화하기 위한 기울기를 계산한다. 계산된 기울기를 이용하여 영상을 세분화한 후에 Glassfire 기법을 적용한다. Glassfire 기법이 적용된 영상과 Ends-in Search Stretching 기법이 적용된 영상을 비교하여 중복되는 영역만을 추출한다. 추출된 영역에 퍼지 이진화 기법과 침식 연산을 적용하여 잡음을 제거하고 결함을 검출한다. 제안된 방법을 세라믹 소재 영상을 대상으로 실험한 결과, 기존의 결함 검출 방법보다 효율적으로 결함이 검출되는 것을 확인할 수 있었다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.289-294
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• 2015

Data analysts explore collections of data to search for valuable information using various techniques and tricks. Garbage in, garbage out is a well-recognized idiom that emphasizes the importance of the quality of data in data analysis. It is therefore crucial to validate the data quality in the early stage of data analysis, and an effective method of evaluating the quality of data is hence required. In this paper, a method to visually characterize the quality of data using the notion of a saliency score is introduced. The saliency score is a measure comprising five indexes that captures certain aspects of data quality. Some experiment results are presented to show the applicability of proposed method.

• Proceedings of KOSOMES biannual meeting
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• 2004.05b
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• pp.1-6
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• 2004

This paper suggests an evaluation of risk level for damage of marine accidents in SRRs. Qualitative analyses in words is sometimes priorior to quantative analyses in numeric symbols. This paper intoduces a concept of fuzzy theory with the plenty of related literature review and AHP in the Korean SRRs of RCC and RSC. The methodology of this paper is max . min composition of fuzzy extensive principle, defuzzifiation is centroid of gravity methods. At the result, the evaluation of risk level is especially over Serious for smarine accident of Taean, Gunsan, Mokpo, Yosu, Tongyoung, Busan SRR. This paper recommends that many Rescue Vessels and Equipments need to the reduction of risk level about those.

• Journal of Navigation and Port Research
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• v.28 no.10 s.96
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• pp.909-915
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• 2004

This paper suggests an evaluation of risk level for damage of marine accidents in SRRs. Qualitative analyses in words is sometimes priorior to quantative analyses in numeric symbols. This paper introduces a concept of fuzzy theory with the plenty of related literature riview and AHP in the Korean SRRs of RCC and RSC. The methodology of this paper is $max{\cdot}min$ composition of fuzzy extensive principle, defuzzifiation is centroid of gravity methods. At the result, the evaluation of risk level is especially over Serious for marine accident of Busan SRRs. This paper recommends that many Rescue Vessels and Equipments need to the reduction of risk level about those.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.97-108
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• 2001

Frauds detection is a difficult problem, requiring huge computer resources and complicated search activities Researchers have struggled with the problem. Even though a fee research approaches have claimed that their solution is much better than others, research community has not found 'the best solution'well fitting every fraud. Because of the evolving nature of the frauds. a novel and self-adapting method should be devised. In this research a new approach is suggested to solving frauds in insurance claims credit card transaction. Based on evolutionary computing approach, the method is itself self-adjusting and evolving enough to generate a new self of decision-makin rules. We believe that this new approach will provide a promising alternative to conventional ones, in terms of computation performance and classification accuracy.

• Journal of KIISE:Software and Applications
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• v.26 no.1
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• pp.130-130
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• 1999

In this paper, we propose a novel design method for improving performance of existing FCM-type clustering algorithms. First, we define the performance measure which focuses on bothcompactness and separation of clusters. Next, we optimize this measure using evolution program.Especially the proposed method has following merits: ① using evolution program, it solves suchproblems as initialization, number of clusters, and convergence to local optimum ② it reduces searchspace and improves convergence speed of algorithm since it represents chromosome with possiblepotential centers which are selected possible candidates of centers by density measure ③ it improvesperformance of clustering algorithm with the performance index which embedded both compactnessand separation Properties ④ it is robust to noise data since it minimizes its effect on center search.