• 한국지능시스템학회논문지
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• 제14권5호
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• pp.655-659
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• 2004

In this literature, the selection of data set among the universe set is carried out with the fuzzy entropy function. By the definition of fuzzy entropy, the fuzzy entropy function is proposed and the proposed fuzzy entropy function is proved through the definition. The proposed fuzzy entropy function calculate the certainty or uncertainty value of data set, hence we can choose the data set that satisfying certain bound or reference. Therefore the reliable data set can be obtained by the proposed fuzzy entropy function. With the simple example we verify that the proposed fuzzy entropy function select reliable data set.

• 한국해양공학회지
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• 제11권1호
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• pp.36-43
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• 1997

Weld bead shape is an important measure for evaluation of weld quality. Many welding parameters have influence on the weld bead shape. The quantitative relationship between welding parameters and bead shape, however, is not determined yet because of their high complexity and many unknown factors. Fuzzy expert system is an advanced expert system which uses fuzzy rules and approximate reasoning. It is a vert useful tool for welding technology because is can process rationally the uncertain and inexact information such as the welding information. In this paper, the empirical and the qualitative relationship between welding parameters and bead shape are analyzed and represented by fuzzy rules. They are converted to the quantitative relationship by use of approximate reasoning of fuzzy expert system. Weld bead shape is estimated from the welding parameters using fuzzy expert system. The result of comparison between measured values of weld bead by welding experiments and the estimates values by fuzzy expert system shows a good consistancy.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.123-128
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• 1996

In this paper, a fuzzy controller is proposed for the operation of stoker-type refuse incinerator with many kinds of uncertain factors. To build the exact mathematical model is very difficult because of the variation of physical/chemical properties of refuse as a fuel and the complexity of the combusiton process. The fuzzy controller consists of fuzzy sensor, fuzzy decision maker and tracking part. The rules based on the professional operators empirical knowledge are made for the control of the boiler evaporation rate, emission gas and refuse throughput. For the performance measure of the proposed fuzzy controller, the model of the incinerator is constructed and the simulation results are given.

• 한국지능시스템학회논문지
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• 제18권2호
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• pp.262-267
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• 2008

The focus of this paper is on devising an efficient clustering task for arbitrary color data. In order to tackle this problem, the inherent uncertainty and vagueness of color are represented by a fuzzy color model. By taking a fuzzy approach to color representation, the proposed model makes a soft decision for the vague regions between neighboring colors. A definition on a three-dimensional fuzzy color ball is introduced, and the degree of membership of color is computed by employing a distance measure between a fuzzy color and color data. With the fuzzy color model, a novel fuzzy clustering algorithm for efficient partition of color data is developed.

• 한국지능시스템학회논문지
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• 제14권3호
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• pp.262-266
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• 2004

일반적으로 Lebesgue 적분에서 성립하지만 퍼지적분에서 성립되지 않는 성질이 몇 가지 있다. 그 중 하나가 선형성이다. 본 논문에서는 선형성 표현식에서 덧셈을 supremum 으로 곱셈을 infimum으로 대신한 퍼지선형성의 정의를 소개하고 구간값을 갖는 함수의 준노름 퍼지적분이 퍼지가법성을 갖는 퍼지 측도와 연속인 준 노름이 saturated 조건을 만족할 때, [Max] 조건을 만족하는 가측함수에 대해 퍼지선형성이 성립함을 보였다.

• 해양환경안전학회:학술대회논문집
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• 해양환경안전학회 2004년도 추계학술발표회
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• pp.83-88
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• 2004

본 연구는 우리나라 수색구조 구역에 대한 해양사고 피해규모에 의한 위험수준을 평가하였다. 이러한 위험수준 평가를 위해 본 연구에서는 전문가 지식에 기반한 퍼지로직과 퍼지측도와 t-준노름 퍼지적분법을 이용하였다. 똔 연구의 퍼지로직은 퍼지 확장원리에 의한 최대최소화 합성이고, 비퍼지화는 무게중심법을 이용하였고, 최종 평가는 t-준노름 퍼지적분댑을 이용하였다. 그 결과 목포, 통영, 부산 수색 구조 구역의 위험수준이 가장 높은 것으로 평가되어, 향후 위험수준을 경감 하기 위해 많은 구조선과 구조장비가 필요 할 것으로 판단된다.

• 한국융합학회논문지
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• 제4권3호
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• pp.35-41
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• 2013

Grouping problem with similarities between DNA sequences are studied. The similaritymeasure and the distance measure showed the complementary characteristics. Distance measure can be obtained by complementing similarity measure, and vice versa. Similarity measure is derived and proved. Usefulness of the proposed similarity measure is applied to grouping problem of 25 cockroach DNA sequences. By calculation of DNA similarity, 25 cockroaches are clustered by four groups, and the results are compared with the previous neighbor-joining method.

• 한국컴퓨터정보학회논문지
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• 제25권3호
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• pp.51-55
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• 2020

본 논문에서는 이미지 복원에 사용되는 기존의 FAM (Fuzzy Associative Memory)에 유사성 학습을 채택하여 개선된 FAM을 제안한다. 이미지 복원은 노이즈가 존재하는 버전에서 원 이미지에 가깝게 복원하는 것을 의미한다. 얼굴 인식과 같은 중요한 적용 문제에서 이 프로세스는 잡음에 강하고 견고하며 빠르며 확장 가능해야한다. 기존의 FAM 은 강력한 퍼지 제어를 통하여 도메인에 적용 할 수 있지만 실제 응용 프로그램에서는 용량 문제가 있지만 단순한 단일 계층 신경망이다. 유사성 측정은 복구 된 이미지와 원본 이미지 사이의 제곱 평균 오차를 최소화하기 위해 FAM 구조의 연결 강도와 관련이 있다. 제안된 알고리즘의 효과는 실험에서 랜덤 노이즈로 인한 오류 크기가 현저히 낮아지는 것을 확인하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1998년도 하계학술대회 논문집 B
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• pp.687-689
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• 1998

This paper represents fundamental developments in Fuzzy and Neural approaches. The Fuzzy Controller(FC) and plant are cascaded in Adaptive framework. Each of which produces its outputs. The adjustable parameters all pertain to the fuzzy controller is implemented as an Adaptive FC to adjust the environments of the plant. There is an error meaure block which is a difference between the actual state and desired state. We introduce error back propagation algorithm in neural method. To speed up convergence, we follow a steepest decent in the sense that each parameter set update leads to a smaller error measure and is learned by this methodology. Inverted pendulum is a typical testbed to measure the effectiveness of nonlinear control system. finally we simulated the adaptive fuzzy controller to be able to bring back to the upright position of the its angle and angular velocity.

• Journal of Information Processing Systems
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• 제15권4호
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• pp.986-1016
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• 2019

Mobile user interface pattern (MUIP) is a kind of structured representation of interaction design knowledge. Several studies have suggested that MUIPs are a proven solution for recurring mobile interface design problems. To facilitate MUIP selection, an effective clustering method is required to discover hidden knowledge of pattern data set. In this paper, we employ the semi-supervised kernel fuzzy c-means clustering (SSKFCM) method to cluster MUIP data. In order to improve the performance of clustering, clustering parameters are optimized by utilizing the global optimization capability of particle swarm optimization (PSO) algorithm. Since the PSO algorithm is easily trapped in local optima, a novel PSO algorithm is presented in this paper. It combines an improved intuitionistic fuzzy entropy measure and a new population search strategy to enhance the population search capability and accelerate the convergence speed. Experimental results show the effectiveness and superiority of the proposed clustering method.