• 한국지구과학회지
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• 제26권2호
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• pp.114-128
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• 2005

Fuzzy information representation of multi-source spatial data is applied to landslide hazard mapping. Information representation based on frequency ratio and non-parametric density estimation is used to construct fuzzy membership functions. Of particular interest is the representation of continuous data for preventing loss of information. The non-parametric density estimation method applied here is a Parzen window estimation that can directly use continuous data without any categorization procedure. The effect of the new continuous data representation method on the final integrated result is evaluated by a validation procedure. To illustrate the proposed scheme, a case study from Jangheung, Korea for landslide hazard mapping is presented. Analysis of the results indicates that the proposed methodology considerably improves prediction capabilities, as compared with the case in traditional continuous data representation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.952-955
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• 1996

It is difficult to determine the feeding rate of coagulant in water treatment process, due to nonlinearity, multivariables and slow response characteristics etc. To deal with this difficulty, the fusion of genetic algorithms and fuzzy inference system was used in determining of feeding rate of coagulant. The genetic algorithms are excellently robust in complex operation problems, since it uses randomized operators and searches for the best chromosome without auxiliary information from a population consists of codings of parameter set. To apply this algorithms, we made the look up table and membership function from the actual operation data of water treatment process. We determined optimum dosages of coagulant (PAC, LAS etc.) by the fuzzy operation, and compared it with the feeding rate of the actual operation data.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권3호
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• pp.242-247
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• 2002

According to increase of the factory-automation(FA) in the field of production, the importance of the autonomous guided vehicle's(AGV) role has also increased. This paper is about an active and effective controller which can flexibly prepare for changeable circumstances. For this study, research about an behavior-based system evolving by itself is also being considered. In this Paper, we constructed an active and effective AGV fuzzy controller to be able to carry out self-organization. To construct it, we tuned suboptimally membership function using a genetic algorithm(GA) and improved the control efficiency by self-correction and the generation of control rules.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 1999년도 가을 학술발표논문집 Vol.26 No.2 (2)
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• pp.327-332
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• 1999

Fuzzy systems, neural networks and genetic algorithms have different origins and thus have differently developed their own unique characteristics. These characteristics can be used as a good complement to the others. Therefore, many researches have been devoted to not only these techniques but also fusion of them. This paper briefly summarizes these three techniques and surveys the researches on fusion of them.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.23-27
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• 2000

In this paper, we propose an emotional evaluation model based on information fusion. This model can transform the physical features of a color pattern to the emotional features. Our proposed model consists of the fuzzy logic system and neural network model. The evaluation values produced by them were fused. The model shows comparable performances to the neural network and fuzzy logic system for the approximation of the nonlinear transforms. We believe the evaluated results of a color pattern can be used to the emotion-based color image retrievals.

• 한국정보통신학회논문지
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• 제15권12호
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• pp.2511-2520
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• 2011

본 논문은 다중 센서 융합의 성능을 높이기 위해 적응형 퍼지-칼만 필터를 적용하고 교차검증법(cross-validation)으로 퍼지시스템 입 출력 소속 함수의 매개변수를 조정하는 방법을 제안한다. 적응형 퍼지-칼만 필터는 가속도의 변화량과 칼만 필터의 잔여오차를 입력으로 시스템잡음, 측정잡음을 추정하여 칼만 이득을 변화시킨다. 적용된 퍼지-칼만 필터는 잡음들을 가우시안 분포로 가정한 이전 방법과 비교하여 비선형/비가우시안 잡음에 강인한 추정 결과를 보여준다. 본 논문에서 제안한 퍼지-칼만 필터를 평가하기 위해 가속도센서/자이로센서를 융합하여 2축 자세추정시스템(Attitude Heading Reference System)을 설계하였고 무인항공기에 사용되는 자세추정센서 NAV420CA-100과 비교하여 성능을 검증하였다.

• 인지과학
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• 제4권1호
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• pp.261-294
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• 1993

대부분의 규칙 기반 전문가 시스템에서 규칙의 갱신과 새로운 규칙의 추가가 다른 규칙에 영향을 주어서는 안된다. 이러한 원리를 규칙의 모듈성이라고 한다. 전문가 시스템에서 증거간의 관계를 알려고 할때, 기존의 전문가 시스템은 정보의 근원이 다른것으로 가정하고 믿음값을 갱신한다. 이러한 가정은 규칙의 모듈성을 위반하게 된다. 본 논문에서는 이러한 문제점을 해결하기 위해 규칙의 모듈성을 보장하는 베이지안 네트워크에 기반을 둔 Fuzzy Belief Network 를 제안한다. Fuzzy Belief Network을 구축하기 위해 노드와 링크 등을 정의하고, 각 노드에서 발생하는 자료의 융합 알고리즘과 자료를 융합한 결과인 믿음값을 모든 노드에 전달하는 확산 알고리즘을 제안한다.

• 대한전기학회논문지
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• 제41권9호
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• pp.1095-1103
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• 1992

An approach to fuse the fuzzy inference system which is able to deal with imprecise and uncertain information and genetic algorithms which display the excellent robustness in complex optimization problems is presented in this paper. In order to combine genetic algorithms and fuzzy inference engine effectively the new reasoning method is suggested. The efficient identification method of fuzzy rules is proposed through the adjustment of search areas of genetic algorithms. The feasibilty of the proposed approach is evaluated through simulation.

• 한국전자통신학회논문지
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• 제10권4호
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• pp.507-512
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• 2015

거리 측정정보를 사용하는 무선위치추정시스템에서 추정기법으로 반복기법기반 근사해를 주로 많이 사용하고 있으나 지역최소문제 및 계산량을 고려해 대안으로 선형 닫힌 형태의 해가 연구되어 왔다. 그러나 각 닫힌 형태의 해는 별도의 특성을 가진 오차요인을 갖고 있으며 이 문제로 인해 그 사용이 제한되기도 한다. 본 논문에서는 대표적인 두 닫힌 형태의 해를 융합하여 각 해가 갖는 오차요인을 서로 상쇄시키는 기법을 제안한다. 두 해를 융합하기 위한 가중치를 각 오차요인이 갖는 오차 특성 기반 퍼지 기법으로 결정하는 방법을 사용한다. 제안된 기법의 성능은 시뮬레이션 기반으로 검증한다.

• 대한원격탐사학회지
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• 제21권5호
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• pp.393-404
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• 2005

As multi-source spatial data fusion mainly deal with various types of spatial data which are specific representations of real world with unequal reliability and incomplete knowledge, proper data representation and uncertainty analysis become more important. In relation to this problem, this paper presents and applies an advanced data representation methodology for different types of spatial data such as categorical and continuous data. To account for the uncertainties of both categorical data and continuous data, fuzzy boundary representation and smoothed kernel density estimation within a fuzzy logic framework are adopted, respectively. To investigate the effects of those data representation on final fusion results, a case study for landslide hazard mapping was carried out on multi-source spatial data sets from Jangheung, Korea. The case study results obtained from the proposed schemes were compared with the results obtained by traditional crisp boundary representation and categorized continuous data representation methods. From the case study results, the proposed scheme showed improved prediction rates than traditional methods and different representation setting resulted in the variation of prediction rates.