• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.11 no.1
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• pp.81-91
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• 1997

본 논문에서는 시스템 모델링이 어렵과 복잡한 자동화 설비를 위한 간단한 지능제어방식을 제안하나. 제안된 방식은 시스템 모델링이 불확실한 시스템에 대하여 입력신호와 직접관계되지 않은 비선형 함수의 동정은 퍼지-신경회로망을 이용하고, 입력신호와 관계되는 비선형 함수는 동정을 하지 않고 임의의 양의 실수로 놓으므로 기존의 전체함수 동정보다 적은량으로 동정할 수 있고, 동정된 정보를 이용하여 비선형 제어기를 설계하는 간단한 제어방식이다. 제안된 제어 방식의 유용성을 확인하기 위하여 자동화 설비에 액츄에이터로 많이 사용되는 직류 서보전동기를 이용한 역진자 시스템에 적용하여 시뮬레이션 및 실험을 하고, 제안된 제어방식을 기존의 신경회로망 제어방식과 제어성능을 비교 검토한다.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3007-3009
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• 2000

In this paper, we design a Multi-Fuzzy model by means of clustering method and genetic algorithms for a nonlinear system. In order to determine structure of the proposed Multi-Fuzzy model. HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy are identified by genetic algorithms. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy model and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1046-1049
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• 1998

This paper deals with the new fault detection technique for transmission line using Neuro-fuzzy Scheme. Neuro-fuzzy Scheme is ANFIS(Adaptive-network Fuzzy Inference System) based on fusion of fuzzy logic and neural networks. The proposed scheme has five layers. Each layer is the component of fuzzy Inference system and performs different action. Using learning method of neural network, fuzzy premise and consequent parameters is tuned properly.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.2
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• pp.192-197
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• 2009

In this paper, we proposed the obstacle avoidance system using a single camera image and LM(Levenberg-Marquart) neural network fuzzy controller. According to a robot technology adapt to various fields of industry and public, the robot has to move using self-navigation and obstacle avoidance algorithms. When the robot moves to target point, obstacle avoidance is must-have technology. So in this paper, we present the algorithm that avoidance method based on fuzzy controller by sensing data and image information from a camera and using the LM neural network to minimize the moving error. And then to verify the system performance of the simulation test.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.1
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• pp.29-35
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• 2004

When an optical pulse is propagated through the atmosphere space, it is attenuated and broadened by the effect of atmospheric turbulence. This pulse broadening is occurred by the fluctuation in the arrival time of pulse at an optical receiver. In digital optical communication, the attenuation is important factor but the pulse broadening is more important. In this paper, thus, we will find the broadening of pulse propagated through the turbulent atmosphere, present it as the function of the structure constant for the refractive index fluctuation, and simulate it to the turbulent strength and the transmission length.

• Journal of Internet Computing and Services
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• v.6 no.3
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• pp.159-170
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• 2005

OC-SVM(One Class Support Vector Machine) avoids solving a full density estimation problem, and instead focuses on a simpler task, estimating quantiles of a data distribution, i.e. its support. OC-SVM seeks to estimate regions where most of data resides and represents the regions as a function of the support vectors, Although OC-SVM is powerful method for data description, it is difficult to incorporate human subjective importance into its estimation process, In order to integrate the importance of each point into the OC-SVM process, we propose a fuzzy version of OC-SVM. In FOC-SVM (Fuzzy One-Class Support Vector Machine), we do not equally treat data points and instead weight data points according to the importance measure of the corresponding objects. That is, we scale the kernel feature vector according to the importance measure of the object so that a kernel feature vector of a less important object should contribute less to the detection process of OC-SVM. We demonstrate the performance of our algorithm on several synthesized data sets, Experimental results showed the promising results.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.20 no.5
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• pp.491-497
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• 2008

The effect of wave and current interactions on jet-like current flowing against waves was investigated based on numerical simulations. The numerical simulations were conducted using a model system of REF/DIF(a wave model) and SHORECIRC(a current model). In the simulations, irregular waves refracted due to the jet-like opposing current were focused along the centerline of current, and the jet-like current was spreaded earlier when the wave heights become larger. The numerical results show that the rapid change of wave height distribution in transverse direction near current inlet plays a significant role to spread the jet-like current. In other words, the radiation stress gradients acting in transverse direction have a more significant effect on the jet-like current than its gradients acting in flowing direction which tend to accelerate the current do. In conclusion, it is indispensible to take into account the interaction between waves and current when the jet-like current such as river mouth meets opposing waves.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.382-382
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• 2011

최근의 극심한 기상이변으로 인하여 발생되는 유출량의 예측에 관한 사항은 치수 이수는 물론 방재의 측면에서도 역시 매우 중요한 관심사로 부각되고 있다. 강우-유출 관계는 유역의 수많은 시 공간적 변수들에 의해 영향을 받기 때문에 매우 복잡하여 예측하기 힘든 요소이며, 과거에는 추계학적 예측모형이나 확정론적 예측모형 혹은 경험적 모형 등을 사용하여 유출량을 예측하였으나 최근에는 인공신경망과 퍼지모형 그리고 유전자 알고리즘과 같은 인공지능기반의 모형들이 많이 사용되고 있다. 하지만 유출량을 예측하고자 할 때 학습자료 및 검정자료로써 사용되는 유출량은 수위-유량 관계곡선식으로부터 구하는 경우가 대부분으로 이는 이렇게 유도된 유출량의 경우 오차가 크기 때문에 그 신뢰성에 문제가 있을 것으로 판단된다. 따라서 본 논문에서는 수위를 직접 예측함으로써 이러한 오차의 문제점을 극복 하고자 한다. Neuro-Fuzzy 모형은 과거자료의 입 출력 패턴에서 정보를 추출하여 지식으로 보유하고, 이를 근거로 새로운 상황에 대한 해답을 제시하도록 하는 인공지능분야의 학습기법으로 인간이 과거의 경험과 훈련으로 지식을 축적하듯이 시스템의 입 출력에 의하여 소속함수를 최적화함으로서 모형의 구조를 스스로 조직화한다. 따라서 수학적 알고리즘의 적용이 어려운 강우와 유출관계를 하천유역이라는 시스템에서 발생된 신호체계의 입 출력패턴으로 간주하고 인간의 사고과정을 근거로 추론과정을 거쳐 수문계의 예측에 적용할 수 있을 것이다. 유전자 알고리즘은 적자생존의 생물학 원리에 바탕을 둔 최적화 기법중의 하나로 자연계의 생명체 중 환경에 잘 적응한 개체가 좀 더 많은 자손을 남길 수 있다는 자연선택 과정과 유전자의 변화를 통해서 좋은 방향으로 발전해 나간다는 자연 진화의 과정인 자연계의 유전자 메커니즘에 바탕을 둔 탐색 알고리즘이다. 즉, 자연계의 유전과 진화 메커니즘을 공학적으로 모델화함으로써 잠재적인 해의 후보들을 모아 군집을 형성한 뒤 서로간의 교배 혹은 변이를 통해서 최적 해를 찾는 계산 모델이다. 이러한 유전자 알고리즘은 전역 샘플링을 중심으로 한 수법으로 해 공간상에서 유전자의 개수만큼 복수의 탐색점을 설정할 뿐만 아니라 교배와 돌연변이 등으로 좁아지는 탐색점 바깥의 영역으로 탐색을 확장할 수 있기 때문에 지역해에 빠질 위험성이 크게 줄어든다. 따라서 예측과 패턴인식에 강한 뉴로퍼지 모형의 해 탐색방법을 유전자 알고리즘을 사용한다면 보다 정확한 해를 찾는 것이 가능할 것으로 판단된다. 따라서 본 논문에서는 선행우량 및 상류의 수위자료로부터 하류의 단시간 수위예측에 관해 연구하였으며, 이를 위해 유전자 알고리즘을 이용항여 소속함수를 최적화 시키는 형태의 Neuro-Fuzzy모형에 대하여 연구하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2757-2763
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• 2015

p-Snake is an energy minimizing algorithm that applies an additional prototype energy to the existing Active Contour Model and is used to extract the contour line in the area where the edge information is unclear. In this paper suggested the creation of a prototype energy field that applies a variable prototype expressed as a combination of circle and straight line primitives, and a fudge function, to improve p-Snake's contour extraction performance. The prototype was defined based on the parts codes entered and the appropriate initial contour was extracted in each primitive zones acquired from the pre-processing process. Then, the primitives variably adjusted to create the prototype and the contour probability based on the distance to the prototype was calculated through the fuzzy function to create the prototype energy field. This was applied to p-Snake to extract the contour from 100 images acquired from various small parts and compared its similarity with the prototype to find that p-Snake made with the adaptive prototype was about 4.6% more precise than the existing Snake method.

• Journal of Korean Society for Geospatial Information Science
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• v.22 no.1
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• pp.13-22
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• 2014

Recently, many civil appeals have been occurred in land management work because of discord between cadastral records and actual land use pattern. it is important to select parcels for land alternation exactly using land information and to evaluate compensation cost according to scenarios for advancing this problem. This study operated GIS spatial overlay based on serial cadastral maps and actual-width of the road and analyzed the number and area of the parcels for land alternation by the land classification and ownership applying fuzzy membership function according to occupation ratio to road. Also compensation cost was calculated according to scenarios using individual public land price information of the parcels for land alternation and was arranged by district as Eup and Myeon according to land classification and ownership. This study can efficiently support the work of the parcels for land alternation complying with the financial condition of local government, by supplying compensation cost according to scenarios to the parcels of land alternation by district as Eup and Myeon.