• The KIPS Transactions:PartB
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• v.8B no.5
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• pp.463-468
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• 2001

We propose a new similarity measure based on relative membership function (RMF). In this paper, the RMF is suggested to represent the relativity between fuzzy subsets easily. Since the shape of the RMF is determined according to the values of its parameters, we can easily represent the relativity between fuzzy subsets by adjusting only the values of its parameters. Hence, we can easily reflect the relativity among individuals or cultural differences when we represent the subjectivity by using the fuzzy subsets. In this case, these parameters may be regarded as feature points for determining the structure of fuzzy subset. In the sequel, the degree of similarity between fuzzy subsets can be quickly computed by using the parameters of the RMF. We use Euclidean distance to compute the degree of similarity between fuzzy subsets represented by the RMF. In the meantime, we present a new linguistic approximation method as an application area of the proposed similarity measure and show its numerical example.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.4
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• pp.815-825
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• 2007

The existing web-based self-directed learning systems are in short for the ability of learning skills assessment. Even worse, hey only give test scores as an indicate for test skills, which is also not a good measure for learning skills assessment and makes it difficult to assess learning skills objectively and to present clear assessment criterion. In this paper, we proposed an improved self-directed learning system using fuzzy logic, which can be controlled by learners themselves and helps to evaluate their on learning process. We also implemented the system on the written examination of Engineer Information Processing. The purposed system lust calculates membership functions of learning tine, learning frequency, testing time, and test score. Using them the final membership functions of learning and test skills are calculated and presented in a graphical, i.e. mon understandable, way to user. The purposed system helps learners to assess their achievement and to plan future schedule, and the survey result on the students used the system also supports that.

• Journal of Advanced Marine Engineering and Technology
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• v.25 no.3
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• pp.623-630
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• 2001

The conventional control techniques based a mathematical model are not well suited for dealing with ill-defined and uncertain system like a linear quadratic control. Recently, fuzzy control has been successfully applied to a wide variety of practical problems such as robot, water purification, automatic train operation system etc. In this paper, a design technique of robust Fuzzy-LQ controller for each subsystem is designed. Secondly , all the subsystem controllers are combined by fuzzy weighted averaging method. Finally the effectiveness of the proposed controller is verified through a series of computer simulations for an inverted pole system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.11a
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• pp.363-366
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• 2000

본 논문에서는 브러쉬없는 직류전동기의 위치제어를 위한 직접적응 퍼지가변구조제어기를 설계한다. 가변구조제어는 시스템의 파라메터 변화나 외란에 둔감한 특성을 갖는 반면 떨림현상의 문제점을 가지고 있다. 떨림현상의 진폭은 시스템의 불확실정보를 최악의 상태로 가정한 후 결정되므로, 기존의 가변구조제어에서는 그 크기가 너무 크다. 또한 이런 불확실한 요소들의 최대값은 찾아내기도 어렵다. 본 논문에서는 불확실한 요소의 최대값을 최적으로 추정하기 위하여 퍼지 추론 기법을 사용한다. 아울러 소속함수의 원소들을 직접적응 기법에 의하여 자동 조정할 수 있는 기법을 추가한다. 이를 통하여 우수한 제어 성능을 얻을 수 있음을 확인한다.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.405-408
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• 2004

본 논문에서는 시간과 부하의 변화에 따라 편안한 승차감과 빠른 속도를 가질 수 있도록 다양한 속도 패턴을 제공하는 퍼지 알고리즘을 실제 공정에 적용할 수 있도록 SoC Design을 하였다. 운송 속도와 승차감은 엘리베이터 속도 패턴을 결정하기 위한 두개의 중요한 요소이며, 본 논문에서는 운송능력을 향상시키기 위해 교통량 변화에 맞춰서 저크를 조정하였다. 여기에서 구현된 퍼지 추론 시스템은 2개의 입력 변수와 1개의 출력을 가진 시스템이다. 전반부는 교통량의 변화를 나타내며, 시간 입력에 대해서 사다리꼴 형태의 소속함수를 사용하였다. 후반부는 입력에 대응되는 속도 패턴으로써, 싱글톤이 후반부에 적용되었다. 본 논문에서 구현 Tool 로는 SoC 설계를 사용하였다. SoC 설계는 현재 그 확장성과 유연성에 뛰어난 장점을 지니고 있으며, 제안된 알고리즘을 모듈로 설계하여 프로그래밍과 실행 사이클을 단축시키는 효과가 있다.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.149-152
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• 2003

플랜트 모델이나 경험에 근거하여 설계된 퍼지제어기를 실제 플랜트에 적용할 경우, 모델링 오차와 플랜트에 대한 관련지식의 부족으로 만족할 만한 제어 결과를 나타내지 못할 경우가 있다. 이 경우 제어성능을 향상시키기 위해 제어기의 제어인자를 다시 조정하여야 하고, 이 조정과정은 시행착오 방법으로 수행되기 때문에 많은 시간과 비용을 필요로 한다. 본 논문에서는 정규화 된 오차와 오차 변화량를 사용하여 플랜트 응답에 따라 입력과 출력의 적절한 스케일 계수를 조정하는 퍼지제어기를 제안한다. 정규화 된 오차를 출력 소속함수의 중심과 폭에 곱해 출력 범위를 재조정하고, 플랜트 응답에 의해 입력의 스케일 계수를 결정한다. 이를 확인하기 위해 2차 플랜트에 적용하여 모의 실험을 수행하였다.

• Journal of Digital Convergence
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• v.12 no.8
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• pp.321-327
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• 2014

Feature selection is the technique to improve the classification performance by using a minimal set by removing features that are not related with each other and characterized by redundancy. This study proposed new feature selection using the distance between the center of gravity of the bounded sum of weighted fuzzy membership functions (BSWFMs) provided by the neural network with weighted fuzzy membership functions (NEWFM) in order to improve the classification performance. The distance-based feature selection selects the minimum features by removing the worst features with the shortest distance between the center of gravity of BSWFMs from the 24 initial features one by one, and then 22 minimum features are selected with the highest performance result. The proposed methodology shows that sensitivity, specificity, and accuracy are 97.7%, 99.7%, and 98.7% with 22 minimum features, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.3
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• pp.378-382
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• 2006

This paper presents an approach to detect premature ventricular contractions(PVC) using the neural network with weighted fuzzy membership functions(NEWFM). NEWFM classifies normal and PVC beats by the trained weighted fuzzy membership functions using wavelet transformed coefficients extracted from the MIT-BIH PVC database. The two most important coefficients are selected by the non-overlap area distribution measurement method to minimize the classification rules that show PVC classification rate of 99.90%. By Presenting locations of the extracted two coefficients based on the R wave location, it is shown that PVC can be detected using only information of the two portions.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.57-66
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• 2011

The purpose of this study is to research into a method of selecting the subject parcel with a change in the category of land given surveying the land alteration state focusing on the present state of road in the government-owned and public land by using the fuzzy membership function and GIS spatial analysis. It selected the old town center of Incheon Jung-gu, and the new downtown & the forest land of Gyeyang-gu as the research subject region, and carried out GIS spatial analysis on a serial cadastral map, urban planning road layer of Korea Land Information System, practical width of road layer of Road Name Address Management System & cadastral data base, and then calculated the suitable index for the subject parcel with a change in the category of land by using the fuzzy membership function with having the critical value as the area ratio of each parcel on a serial cadastral map that was incorporated into road layer or practical width of road layer. It finally selected the parcel, which is different in land category from the real land usage, as the final subject parcel for altering land category, by using the screen of visualizing the suitable index and the aerial ortho photograph. As a result of the final selection, the fuzzy GIS spatial analysis method, which was suggested in this study, is judged to be efficient in the selection period and the methodology compared to the existing manual method. It could be confirmed to be more suitable method for downtown than forest land and for the new downtown than the old town center.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.11
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• pp.5379-5388
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• 2012

In fuzzy modeling for nonlinear process, the fuzzy rules are typically formed by selection of the input variables, the number of space division and membership functions. The Generation of fuzzy rules for nonlinear processes have the problem that the number of fuzzy rules exponentially increases. To solve this problem, complex nonlinear process can be modeled by generating the fuzzy rules by means of fuzzy division of input space. Therefore, in this paper, rules of non-fuzzy inference systems are generated by partitioning the input space in the scatter form using HCM clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of HCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the consequence parameters of each rule are identified by the standard least-squares method. And lastly, we evaluate the performance and the nonlinear characteristics using the data widely used in nonlinear process. Through this experiment, we showed that high-dimensional nonlinear systems can be modeled by a very small number of rules.