• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.150-153
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• 2000

본 논문에서는 퍼지규칙의 수가 적고, 결론부가 선형식으로 표현되는 TSK 퍼지시스템을 이용한다. 본 논문에서 제안되는 적응제어 방법은 규범모델 적응제어 기법을 응용한 것으로 Lyapunov함수를 이용하여 안정성문제를 해결하면서 동시에 최적의 적응법칙을 유도 할 수 있도록 설계되었다. 그리고 역진자 시스템에 대해서 시뮬레이션을 통해 제안된 적응 퍼지제어기의 설계 방법이 유효함을 보인다.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.367-374
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• 1999

This paper suggests an integrated method based on concept ascension and attribute reduction for efficient induction of decision rules from a large database. We study an automatic scheme to generate concept trees by a clustering technique, a method for generalizing databases by the concept ascension technique, an optimal reduction method by means of attributes reduction using the sibmificance of attributes, and an efficient way of reduction of attribute values applying the discernible matrix and functions. The method can be used for the decision making tasks such as an investment planning or price evaluation, the construction of knowledge bases for diagnosis of defects or medical diagnosis, data analysis such as marketing or experimental data, information retrieval for high level inquiries, and so on.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.10a
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• pp.864-867
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• 2019

본 연구에서는 러프 근사화 개념을 활용하여 섬망 환자를 사전에 구별할 수 있는 임상적 지식을 유도할 수 있는 방법을 제안하였다. 실험 결과에서는 평균 섬망기간이 13일 이상 유지되는 6가지 임상적 분류기준을 유도하였고, 통계적 5겹 교차검정 실험을 통해 73%의 분류 성능을 제공함을 확인하였다.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.835-845
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• 2013

Association rule of data mining techniques is the method to quantify the relevance between a set of items in a big database, andhas been applied in various fields like manufacturing industry, shopping mall, healthcare, insurance, and education. Philosophers of science have proposed interestingness measures for various kinds of patterns, analyzed their theoretical properties, evaluated them empirically, and suggested strategies to select appropriate measures for particular domains and requirements. Such interestingness measures are divided into objective, subjective, and semantic measures. Objective measures are based on data used in the discovery process and are typically motivated by statistical considerations. Subjective measures take into account not only the data but also the knowledge and interests of users who examine the pattern, while semantic measures additionally take into account utility and actionability. In a very different context, researchers have devoted a lot of attention to measures of confirmation or evidential support. The focus in this paper was on asymmetric confirmation measures, and we compared confirmation measures with basic association thresholds using some simulation data. As the result, we could distinguish the direction of association rule by confirmation measures, and interpret degree of association operationally by them. Futhermore, the result showed that the measure by Rips and that by Kemeny and Oppenheim were better than other confirmation measures.

• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.105-115
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• 2007

Data mining extracts interesting knowledge from a large database. Among numerous data mining techniques, research work is primarily concentrated on clustering and association rules. The clustering technique of the active research topics mainly deals with analyzing spatial and attribute data. And, the technique of association rules deals with identifying frequent patterns. There was an advanced apriori algorithm using an existing bit-clustering algorithm. In an effort to identify an alternative algorithm to improve apriori, we investigated FP-Growth and discussed the possibility of adopting bit-clustering as the alternative method to solve the problems with FP-Growth. FP-Growth using bit-clustering demonstrated better performance than the existing method. We used chess data in our experiments. Chess data were used in the pattern mining evaluation. We made a creation of FP-Tree with different minimum support values. In the case of high minimum support values, similar results that the existing techniques demonstrated were obtained. In other cases, however, the performance of the technique proposed in this paper showed better results in comparison with the existing technique. As a result, the technique proposed in this paper was considered to lead to higher performance. In addition, the method to apply bit-clustering to GML data was proposed.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.21 no.1
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• pp.54-62
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• 2009

The present study investigates the behaviour of overtopping flows falling on the leeside of a caisson breakwater with dissipating blocks through laboratory measurements. The falling overtopping flows in the leeside are expected to directly affect the leeside stability of the breakwater. This study focuses on not the resultant stability but the characteristic pattern of the overtopping flows depending on wave conditions through examining front velocity and plunging distance in the leeside. Regular waves were used to investigate the dependence of the overtopping flow pattern on wave conditions and a modified image velocimetry combining the shadowgraphy and cross-correlation method was employed for measurements of image and velocity. From the measurements, it is shown that the plunging distance and front velocity of the overtopping flow in the breakwater leeside increase as the wave period or height increases. From non-dimensional relationships between the variables, empirical formula for the velocity and overtopping distance are suggested.

• Journal of Information Technology Applications and Management
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• v.17 no.2
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• pp.71-90
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• 2010

Electronic learning(or e-learning) has created hype for companies, universities, and other educational institutions. It has led to the phenomenal growth in the use of web-based learning and experimentation with multimedia, video conferencing, and internet-based technologies. Many researchers are interested in the factors that affect to the performance of e-learning or e-learning services. In this sense, this study is aimed at proposing e-learning system reuse prediction models in which e-learner intention to reuse influence factors(i.e., system accessibility, system stability, information clarity, information validity, self-regulated efficacy, computer self-efficacy, perceived usefulness, perceived ease of use, flow, and parental expectation) affect e-learner intention to reuse positively. A web survey was conducted for the full members of the e-learning education institute A in Seoul, Republic of Korea, an exclusive e-learning company that provides real time video lectures via the desktop conferencing system. The web survey was conducted for 20 days from November 5, 2009, through the e-learning web site of the company A. In this study, three data mining techniques were used : the multivariate discriminant analysis, CART, and C5.0 algorithm. This study was conducted to provide the e-learning service providers, e-learning operators, and contents developers with marketing and management strategies for improving the e-learning service companies, based on the data mining analysis results.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.3
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• pp.619-626
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• 2007

Constructive induction is a technique to draw useful attributes from given primitive attributes to classify given examples more efficiently. Useful attributes are obtained from given primitive attributes by applying appropriate operators to them. The paper proposes a constructive induction approach for a GA-based inductive learning environment that learns classification rules that ate similar to rules used in PROSPECTOR from given examples. The paper explains our constructive induction approach in details, centering on operators to combine primitive attributes and methods to evaluate the usefulness of derived attributes, and presents the results of various experiments performed to evaluate the effect of our constructive induction approach on the GA-based learning environment.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.3 s.303
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• pp.11-16
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• 2005

This paper proposed a new IMC-PID controller design method using the loop shaping method. By the application of the loop shaping method for IMC-PID controller which has only one design parameter and guarantees internal stability, we can not only consider such design specifications as gain margin, phases margin, and sensitivity functions but also obtain the loop gain by setting up the relationships between design specifications and design parameters. A systematic method to select design parameters of IMC-PID controller in order to meet the design specifications is suggested and its effectiveness is examined by the case study and analysis.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.2
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• pp.16-24
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• 2010

This paper is proposed a novel fuzzy disturbance observer based on backstepping method for nonlinear systems with unknown disturbance. Using fuzzy logic systems, a fuzzy disturbance observer with the disturbance observation input is introduced for unknown disturbance. To guarantee that the proposed disturbance observer estimates the unknown disturbance, the disturbance observation error dynamic system is employed. Under the framework of the backstepping design, the fuzzy disturbance observer is constructed recursively and an adaptive laws and the disturbance observation input are derived. Numerical examples are given to demonstrate the validity of our proposed disturbance observer for nonlinear systems.