• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.272-277
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• 1998

If we want to compare the form of two objects, the human vision takes into account the parameter's width/length/height at the same time. however, the machine needs to compare width then lengths and finally height. In each comparison the machine considers only one character. The goal of this paper is to imitate the human manner of comparison and recognition by using two or three characters instead of one during the comparison. The ellipse is a first approach of comparison because it provides us a general and a simple relation that can link two parameters that are the half axis of the ellipse. Indeed, we assimilate each character to a half axis of the ellipse and the result is a geometrical figure that varies according to values of the two characters.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.19-22
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• 2001

In this paper, Streaming Current Monitor (SCM), Pilot Filter (PF) and Coagulant Feeding System(CFS) for fuzzy neural network are used as a coagulation control method in WTP and the results are compared. Several parameters such as coagulant dosage, pH, and turbidity have been changed to find the response characteristic of each equipment. SCM, PF and CFS responded for certain parameters but the range of sensitivity was different each other. It is demonstrated that WTP will be operated more efficiently when SCM, PF and CFS are used as coagulation control strategy.

• The Journal of Information Systems
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• v.4
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• pp.27-39
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• 1995

This study tests the fuzzy linear regression model to see if there is a performance difference between it and the classical linear regression model. These results show that FLR was better as f forecasting technique when compared with CLR. Another important find in the test of the two different regression methods is that they generate two different predicted P/E ratios from expected value test, variance test and error test of two different regressions, though we can not see a significant difference between two regression models doing test in error measurements (GMRAE, MAPE, MSE, MAD). So, in this financial setting we can conclude that FLR is not superior to CLR, comparing and testing between the t재 different regression models. However, FLR is better than CLR in the error measurements.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.126-132
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• 2000

This paper presents a facial expression recognition based on Gabor wavelets that uses a fuzzy C-means(FCM) clustering algorithm and neural network. Features of facial expressions are extracted to two steps. In the first step, Gabor wavelet representation can provide edges extraction of major face components using the average value of the image's 2-D Gabor wavelet coefficient histogram. In the next step, we extract sparse features of facial expressions from the extracted edge information using FCM clustering algorithm. The result of facial expression recognition is compared with dimensional values of internal stated derived from semantic ratings of words related to emotion. The dimensional model can recognize not only six facial expressions related to Ekman's basic emotions, but also expressions of various internal states.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.117-122
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• 1992

The fuzzy-neural hybrid control system utilizing the fuzzy-neural network(FNN) will be presented in this paper. The basic structure of the controller is the parallel combination of a conventional P-controller and a FNN. Such a combination can guarantee the stability of a plant at initial stage before the rules are completely created. And a method how to automatically tunning the parameters of the FNN will be proposed with error back-propagation(BP) algorithm. Finally the effectiveness of the proposed strategy will be verified by computer simulations using a two DOF robot manipulator.

• Journal of the Earthquake Engineering Society of Korea
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• v.9 no.2 s.42
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• pp.7-15
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• 2005

Numerical analysis model is proposed to predict the dynamic behavior of a single-degree-of-freedom structure that is equipped with hybrid base isolation system. Hybrid base isolation system is composed of friction pendulum systems (FPS) and a magnetorheological (MR) damper. A neuro-fuzzy model is used to represent dynamic behavior of the MR damper. Fuzzy model of the MR damper is trained by ANFIS (Adaptive Neuro-Fuzzy Inference System) using various displacement, velocity, and voltage combinations that are obtained from a series of performance tests. Modelling of the FPS is carried out with a nonlinear analytical equation that is derived in this study and neuro-fuzzy training. Fuzzy logic controller is employed to control the command voltage that is sent to MR damper. The dynamic responses of experimental structure subjected to various earthquake excitations are compared with numerically simulated results using neuro-fuzzy modeling method. Numerical simulation using neuro-fuzzy models of the MR damper and FPS predict response of the hybrid base isolation system very well.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.472-472
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• 2000

An analog signal conditioner using fuzzy logic technique, which has multiple-input and multiple-output terminals, is proposed in this paper. The proposed signal conditioner can be employed to linearly translate the level of signals to a standard voltage signal (1-5V) and convert the form of signals to a standard current signal (4-20mA). The implementation method based on the use of a commercial 8-bit microcontroller, the analog-to-digital (A/D) converters, the digital-to-analog (D/A) converters and the voltage-to-current (V/I) converter. The simulation result and the experimental results are presented, which further confirm the feasibility of this approach.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.110-115
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• 2006

In pure P2P environment, it is possible to provide service by using a little real-time information without using accumulated information. But in case of using only a little information that was locally collected, quality of recommendation service can be fallen-off. Therefore, it is necessary to study a method to improve qualify of recommendation service by using users' context information. But because a great volume of users' context information can be recognized in a moment, there can be a scalability problem and there are limitations in supporting differentiated services according to fields and items. In this paper, we solved the scalability problem by clustering context information per each service field and classifying it per each user, using SOM. In addition, we could recommend proper services for users by quantifying the context information of the users belonging to the similar classification to the service requester among classified data and then using collaborative filtering.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.278-283
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• 1998

The interval approach to the linguistic expression coding nears us to the human idea. Thus, what seems "weak" for a person can appear very weak for another person or for the same person in others circumstances. However, the utilization of intervals is not restrained to the cases of linguistic expression coding. Indeed, the interval can facilitate the solution of several problems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.291-298
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• 2020

The power generation of a PV system changes according to the weather variables, such as solar radiation and temperature. In particular, the output characteristics of photovoltaic systems, which are sensitive to changes in solar radiation, can be produced effectively and reliably in various weather conditions through MPPT (Maximum Power Point Tracking) control. This paper proposes a fuzzy-based MPPT control method to improve the efficiency and stability of the power production from a solar system. To verify the performance of the proposed method, under the same weather environment, the efficiency and stability of the newly proposed fuzzy logic were compared and evaluated empirically with P&O (Perturb and Observe), a representative algorithm of MPPT control. Furthermore, the circuits designed to improve the reliability and reliability of the hardware were manufactured from Printed Circuit Boards (PCB) to conduct experiments. Based on the results of the experiment during a certain period, the fuzzy-based MPPT proposed in this paper improved the efficiency by more than 4.4% compared to the MPPT based on the existing P&O algorithm and decreased the fluctuation width by more than 39.7% at the maximum power point.