• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.449-449
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• 2000

Many researchers have studied architectures for non-Neumann's computers because of escaping its bottleneck. To avoid the bottleneck, a neuron-based computer has been developed. The computer has only neurons and their connections, which are constructed of the learning. But still it has information processing facilities, and at the same time, it is like as a simplified brain to make inference; it is called "neuron-computer". No instructions are considered in any neural network usually; however, to complete complex processing on restricted computing resources, the processing must be reduced to primitive actions. Therefore, we introduce the instructions to the neuron-computer, in which the most important function is implications. There is an implication represented by binary-operators, but general implications for multi-value or fuzzy logics can't be done. Therefore, we need to use Lukasiewicz' operator at least. We investigated a neuron-computer having instructions for general implications. If we use the computer, the effective inferences base on multi-value logic is executed rapidly in a small logical unit.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권9호
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• pp.4336-4354
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• 2018

Fuzzy C-means (FCM) algorithm is a most usually technique for medical image segmentation. But conventional FCM fails to perform well enough on magnetic resonance imaging (MRI) data with the noise and intensity inhomogeneity (IIH). In the paper, we propose a Gamma correction conditional FCM algorithm with spatial information (GcsFCM) to solve this problem. Firstly, the pre-processing, Gamma correction, is introduced to enhance the details of images. Secondly, the spatial information is introduced to reduce the effect of noise. Then we introduce the effective neighborhood mechanism into the local space information to improve the robustness for the noise and inhomogeneity. And the mechanism describes the degree of participation in generating local membership values and building clusters. Finally, the adjustment mechanism and the spatial information are combined into the weighted membership function. Experimental results on four image volumes with noise and IIH indicate that the proposed GcsFCM algorithm is more effective and robust to noise and IIH than the FCM, sFCM and csFCM algorithms.

• 한국지능시스템학회논문지
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• 제15권3호
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• pp.369-374
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• 2005

현재 선박에서 항해사에게 항로정보를 제공하는 장비는 ECDIS와 GPS 플로터가 많이 사용되고 있으나 자동항로생성 및 항로설명기능이 없어 숙련된 항해사만 사용할 수 있는 문제가 있으며, 특히 종이해도의 대체 시스템인 ECDIS에 사용되는 ENC를 이용한 자동항로생성 및 항로설명에 관한 연구는 없는 실정이다. ENC는 IHO에서 정의한 S-52, S-57 표준포멧을 기반으로 제작된다. 본 논문에서는 ENC의 해도데이터와 GPS의 위치데이터, Anemometer의 풍향${\cdot}$풍속데이터를 이용하여 현 위치에서 목적지까지의 최적항로를 설계하여 안내해주는 항해안내시스템(NGS)을 구축하였고 시뮬레이션을 통하여 그 유효성을 확인하였다.

• 산업경영시스템학회지
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• 제35권4호
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• pp.194-201
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• 2012

Because the difference between products and services are getting less and less, service and manufacturing companies' efforts are increasingly focused on utilizing services to satisfy customers' needs under today's competitive market environment. The value of services depends on service reliability that is identified by satisfaction derived from the relationship between customer needs and service providers. In this paper, we extend concepts from the fault tree analysis for reliability analysis of tangible systems to services. We use an event-based process model to facilitate service design and represent the relationships between functions and failures in a service. The objective of this research is to propose a method for evaluating service reliability based on service processes using service blueprint and FTA. We can identify the failure mode of service in a service delivery process with a service blueprint. The fuzzy membership function is used to characterize the probability of failure based on linguistic terms. FTA is employed to estimate the reliability of service delivery processes with risk factors that are represented as potential failure causes. To demonstrate implementation of the proposed method, we use a case study involving a typical automotive service operation.

• Journal of Electrical Engineering and information Science
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• 제3권3호
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• pp.355-365
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• 1998

The purposes of this study are to propose a network for the characterizing of the input data and to show how to design predictive neural net재가 expert system which doesn't need previous knowledge base. We derived this network from the radial basis function networks(RBFN), and named it as a statistical EBFN. The proposed network can replace the statistical methods for analyzing dynamic relations between target disease and other parameters in medical studies. We compared statistical RBFN with the probabilistic neural network(PNN) and fuzzy logic(FL). And we testified our method in the diabetes prediction and compared our method with the well-known multilayer perceptron(MLP) neural network one, and showed good performance of our network. At last, we developed the diabetes prediction expert system based on the proposed statistical RBFN without previous knowledge base. Not only the applicability of the characterizing of parameters related to diabetes and construction of the diabetes prediction expert system but also wide applicabilities has the proposed statistical RBFN to other similar problems.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.37-43
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• 2003

Current Internet system of the entrance exam information to the university that is depending on searching key to solve the overloaded problem in the network and DB server or other tools to support HTML edit, haven't satisfied user's wants by supplying uniformed searching system. So this thesis will establish EEIS(Entrance Examination Information System) to prevent database overload phenomena when many users request a great amount of data at the same time and improve the decrease of speed and overload problem in DB server. EEIS playa role of bridge between outside client and DB server by placing VVS(Virtual View Server) between web server and DB server. By that method this system give users several usefulness in convenience and variety by supplying realtime data searching function to user. EEIS also give inner system manager more efficiency and speed in control the management system by solving those problem. This system is design and implementation to satisfy user's desire and give them more convenience and bring up the confidence of university that adopt this system at the end.

• 한국지능시스템학회논문지
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• 제12권1호
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• pp.67-72
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• 2002

고수준의 정보 서비스를 제공하기 위해서는 소프트웨어의 고품질화를 추구하여야 한다. 기존에 개발된 품질측정방법들은 모듈내에 포함되어 있는 요인항목들을 서로 다른 관점에서 개별적으로 측정하고있어 통합적인 평가방법이 필요하다. 따라서 본 논문에서는 다수의 측정 방법들을 모두 수용할 수 있는 모델을 제안한다. 제안된 모델은 비율척도들을 선택하고, 러프논리를 이용하여 그들의 중요도를 산출한다. 다음으로 모듈의 품질도를 측정하기 위해서 퍼지적분을 이용하여 척도들의 중요도와 측정값을 종합한다. 마지막으로 척도들과 산출된 품질도의 상관관계를 분석하고, 통계적 방법으로 제안된 모델의 타당성을 보인다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.249-255
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• 2000

HRIV(Hybrid Rule-Interval Variation) method is presented to stabilize a class of nonlinear systems, where SMC(Sliding Mode Control) and ADC (ADaptive Control) schemes are incorporated to overcome the unstable characteristics of a conventional FLC(Fuzzy Logic Control). HRIV method consists of two modes: I-mode (Integral Sliding Mode PLC) and R-mode(RIV method). In I-mode, SMC is used to compensate for MAE(Minimum Approximation Error) caused by the heuristic characteristics of FLC. In R-mode, RIV method reduces interval lengths of rules as states converge to an equilibrium point, which makes the defined Lyapunov function candidate negative semi-definite without considering MAE, and the new uncertain parameters generated in R-mode are compensated by SMC. In RIV method, the overcontraction problem that the states are out of a rule-table can happen by the excessive reduction of rule intervals, which is solved with a dynamic modification of rule-intervals and a transition to I-mode. Especially, HRIV method has advantages to use the analytic upper bound of MAE and to reduce Its effect in the control input, compared with the previous researches. Finally, the proposed method is applied to stabilize a simple nonlinear system and a modified inverted pendulum system in simulation experiments.

• 대한전기학회논문지:전력기술부문A
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• 제52권8호
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• pp.471-480
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• 2003

The design of a measurement system to perform Harmonic State Estimation (HSE) is a very complex problem. Among the reasons for its complexity are the system size, conflicting requirements of estimator accuracy, reliability in the presence of transducer noise and data communication failures, adaptability to change in the network topology and cost minimization. In particular, the number of harmonic instruments available is always limited. Therefore, a systematic procedure is needed to design the optimal placement of measurement points. This paper presents a new HSE algorithm which is based on an optimal placement of measurement points using Genetic Algorithms (GAs) which is widely used in areas such as: optimization of the objective function, learning of neural networks, tuning of fuzzy membership functions, machine learning, system identification and control. This HSE has been applied to the Simulation Test Power System for the validation of the new HSE algorithm. The study results have indicated an economical and effective method for optimal placement of measurement points using Genetic Algorithms (GAs) in the Harmonic State Estimation (HSE).

• 한국통신학회논문지
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• 제25권10A호
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• pp.1512-1520
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• 2000

무선 통신망은 음성위주의 아날로그 방식에서 출발하여, 다양한 서버스 능력을 갖는 디지럴 방식으로 진화되고 있으며 궁극적으로는 멀티미디어 서비스가 가능한 IMT -2000으로 발전할 것이다. 무선망에서 멀티미디어 서비스를 제공하기 위해서는 한정된 무선 대역폭을 트래픽 특성에 따라 동적으로 활용할 수 있는 방안이 요구된다. 본 논문에서는 IMT - 2000 환경에서 이동체의 이동 방향을 추정하여 이를 근거로 대역폭을 예약하고, 멀티미디어 트래픽을 전송하는 대역 할당 및 호 수락 제어 기법을 제안한다. 이 기법은 수신 신호 세기(RSS: Received Si맹a1 Strength) 이외에 이동체와 기지국간이 거리, 이동체의 이동방향, 이동체의 이전위치와 같은 부정확한 다수의 파라미터를 동시에 고려하는 퍼지 다기준(multi-criteria) 의사 결정 방법을 이용하여 이동체의 위치를 추정한다. 시뮬레이션에 의해 성능을 분석하였다.