• KIPS Transactions on Software and Data Engineering
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• v.2 no.8
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• pp.527-534
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• 2013

The software is changed according to the changing businesses and the user requirement, it involves increasing complexity and cost. Considering the repetitive changes required for the software, replacement is more efficient than maintenance at some point. In this study, the replacement time was predicted using the service dissatisfaction index and replacement point assessment index by the software group for each task. First, fuzzy inference was used to develop the method and indicator for the user's service level dissatisfaction. Second, the replacement point assessment method was established considering the quality, costs, and new technology of the software. Third, a replacement time prediction technique that used the gap between the user service measurement and replacement point assessment values was proposed. The results of the case study with the business solutions of three organizations, which was conducted to verify the validity of the proposed prediction technique in this study, showed that the service dissatisfaction index decreased by approximately 16% and the replacement point assessment index increased by approximately 9%.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.119-125
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• 2015

A concentration meter is widely used at purification plants, sewage treatment plants and waste water treatment plants to sort and transfer high concentration sludge and to control the amount of chemical dosage. When the strange substance is contained in the sludge, however, the attenuation of ultrasonic wave could be increased or not be transmitted to the receiver. At that case, the value of concentration meter is higher than the actual density value or vibrated up and down. It has also been difficult to automate the residuals treatment process according to the problems as sludge attachment or damage of a sensor. Multi-beam ultrasonic concentration meter has been developed to solve these problems, but the failure of the ultrasonic beam of a specific concentration measurement value degrade the performance of the entire system. This paper proposes the method to improve the accuracy of sludge concentration rate by choosing reliable sensor values and learning them by proposed algorithm. The prediction algorithm is chosen as neuro-fuzzy model, which is tested by the various experiments.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1924-1925
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• 2011

본 논문에서는 비선형 기동을 하는 기동표적의 추정된 잡음을 분석하여 표적의 기동패턴을 분석하는 알고리즘을 제시하고자 한다. 기동표적의 추정위치와 측정치에서 발생하는 잡음을 가속도와 순수 잡음으로 분리하고 분리된 성분을 분석하여 표적의 기동 패턴을 인식하고 동시에 추적을 실시하는 알고리즘을 구성한다. 잡음의 분리는 퍼지 클러스터링(FCM : Fuzzy C-means Clustering) 기법을 이용하여 적절한 추정값을 이용한다. 추정된 표적의 속도와 가속도, 잡음을 재 구성하여 기동표적의 기동패턴을 분석하고, 동시에 추적을 실시한다. 위의 과정을 통해 가속도를 분리한 후 비선형성을 지닌 기동표적의 기동패턴을 선형화 하여 칼만필터를 이용 잡음을 분리하고 가속도를 다시 보상하여 추적 알로리즘을 구성한다. 그리고 제안된 알고리즘의 수행 가능성을 보여 주기 위하여 몇 가지 예를 제시하였다.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.131-138
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• 1998

In usual statistical data analysis, we describe statistical data by exact values. However, in modem complex and large-scale systems, it is difficult to treat the systems using only exact data. In this paper, we define these data as fuzzy data(ie. Linguistic variable applied to make the member-ship function.) and Propose a new method to get an analysis of fuzzy survey data based on the maximum entropy Principle. Also, we propose a new method of discrimination by measuring distance between a distribution of the stable state and estimated distribution of the present state using the Kullback - Leibler information. Furthermore, we investigate the validity of our method by computer simulations under realistic situations.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.95-98
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• 1998

초음파센서는 저렴성, 단순한 구조, 기계적 강인성, 사용상의 적은 제약 등의 이점 때문에 다양한 응용분야에 적용된다. 물체의 인식에 초음파센서를 사용하기에는 낮은 분해능을 초래하는 불량한 방향성과 측정오류를 유발하는 반사성의 어려움을 내재하고 있다. 이런 문제를 개선하기 위해서 다양한 센사의 배열형태에서 많은 수의 센서를 사용하거나, 일정 수의 센서를 사용할 경우에는 센서의 배열을 기계적으로 이동시킨다. 본 논문에서는 물체의 패턴인식에 있어서 가장 기본적인 거리, 물체크기, 물체각도 값을 얻기 위해 간단하게 구성된 전자회로를 부가하여 초음파센서의 송출전압을 여러 단계로 변경시켜 얻어낸 데이터에 뉴로퍼지 기반의 지능적 계산 알고리즘을 적용하여 개선된 결과를 얻는다.

• Journal of Korea Port Economic Association
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• v.26 no.2
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• pp.82-98
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• 2010

The purpose of this paper is to suggest the efficiency measurement way of Korean seaport by using Average Index Transformation model of fuzzy DEA(Data Envelopment Analysis). Two inputs[cargo handling capacity, and berthing capacity], and outputs[cargo handling amount, and the number of ship calls] are used in 1995 and 2004 for 26 Korean seaports. Empirical main results are as follows: First, Tongyung, Gohyun, Okpo, and Sogcho Ports are efficient, and Yeasu Port shows the high efficiency level over 95% under input oriented CCR model. Gohyun and Sogcho Ports showed the most efficient score under average index transformation model. Okpo and Yeasu Ports increased their efficiency scores as the lamda(λ) values are up. The empirical results of fuzzy DEA average index transformation model for Wando, Yeasu, and Seoguipo ports showed that if the lamda values are higher, the efficiency scores are also higher. The main policy implication based on the findings of this study is that the management manager of Ministry of Land, Transport and Maritime Affairs in Korea should introduce the fuzzy DEA average index transformation model for deciding the size of inputs including the port investment amount and evaluating the port efficiency.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.603-608
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• 2009

In this paper, a similarity measure between interval-valued vague sets is proposed. In the interval-valued vague sets representation, the upper bound and the lower bound of a vague set are represented as intervals of interval-valued fuzzy set respectively. Proposed method combines the concept of geometric distance and the center-of-gravity point of interval-valued vague set to evaluate the degree of similarity between interval-valued vague sets. We also prove three properties of the proposed similarity measure. It provides a useful way to measure the degree of similarity between interval-valued vague sets.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2301-2306
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• 2015

The time to address the exabytes of data has come as the information age accelerates. Big data transfer technology is essential for processing large amounts of data. This paper posits to transfer big data in the optimal conditions by the proposed algorithm for predicting the optimal combination of Pipelining, Concurrency, and Parallelism (PCP), which are major functions of GridFTP. In addition, the author introduced a simple design process of Takagi-Sugeno-Kang (TSK) fuzzy model and designed a model for predicting transfer throughput with optimal combination of Pipelining, Concurrency and Parallelism. Hence, the author evaluated the model of the proposed algorithm and the TSK model to prove the superiority.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.485-490
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• 2004

In data representation, the clustering performs a grouping process which combines given data into some similar clusters. The various similarity measures have been used in many researches. But, the validity of clustering results is subjective and ambiguous, because of difficulty and shortage about objective criterion of clustering. The fuzzy clustering provides a good method for subjective clustering problems. It performs clustering through the similarity matrix which has fuzzy membership value for assigning each object. In this paper, for objective fuzzy clustering, the clustering algorithm which joins principal components analysis as a dimension reduction model with bayesian learning as a statistical learning theory. For performance evaluation of proposed algorithm, Iris and Glass identification data from UCI Machine Learning repository are used. The experimental results shows a happy outcome of proposed model.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.185-190
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• 2009

In this paper, an observer-based intelligent controller for the nonlinear networked control systems with packet loss is proposed for wireless sensor network. For the intelligent control of the nonlinear system, it uses the fuzzy system with Takagi-Sugeno (T-S) fuzzy model. The observer is designed for the fuzzy networked control system, and the output feedback controller is proposed for the stability of estimates and errors. The stability condition of the closed-loop system with the proposed controller is represented to the linear matrix inequality (LMI) form, and the observer and control gain are obtained by LMI. An example is given to show the verification discussed throughout the paper.