• Journal of the Korea Safety Management & Science
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• v.10 no.1
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• pp.67-73
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• 2008

National Education Information System (NEIS) is an ambitious reform project that can improve the competitiveness and performance of education field and to link administrational work of between schools and their senior administration offices via internet. NEIS is introduced to lighten the teachers' overburden, to standardize the work process and to bring better quality education to each classroom and make it possible for those involved in education to resolve any related educational problem on line. This paper aims to construct a hierarchy model consisting of key factors such as technological and administrative factors for the effective use of NEIS and to evaluate the relative importance among key factors using fuzzy AHP technique included fuzzy concepts. Eventually, the analysis results can be utilized to develop the future improvement strategy of NEIS and to satisfy the users.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.3
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• pp.165-170
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• 2011

Due to advances in hardware performance, user-friendly interfaces are becoming one of the major concerns in information systems. Linguistic conversation is a very natural way of human communications. Fuzzy techniques have been employed to liaison the discrepancy between the qualitative linguistic terms and quantitative computerized data. This paper deals with linguistic queries using clustering results on data sets, which are intended to retrieve the close clusters or distant clusters from the clustering results. In order to support such queries, a fuzzy technique-based method is proposed. The method introduces distance membership functions, namely, close and distant membership functions which transform the metric distance between two objects into the degree of closeness or farness, respectively. In order to measure the degree of closeness or farness between two clusters, both cluster closeness measure and cluster farness measure which incorporate distance membership function and cluster memberships are considered. For the flexibility of clustering, fuzzy clusters are assumed to be formed. This allows us to linguistically query close or distant clusters by constructing fuzzy relation based on the measures.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.3
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• pp.57-66
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• 2001

This paper resents a control approach for designing a fuzzy-PI controller for a synchronous generator excitation and SVC system A combination of thyristor-controlled reactors and fixed capacitors (TCR-FC) type SVC is recognized as having the must fiexible control and high speed response, which has been widely utilized in power systems, is considered and designed to improve the response of a synchronous generator, as well as controlling the system voltage A Fuzzy-PI controller for SVC system was proposed in this paper. The PI gain parameters of the proposed Fuzzy-PI controller which is a special type of PI ones are self-tuned by fuzzy inference technique. It is natural that the fuzzy inference technique should be barred on humans intuitions and empirical knowledge. Nonetheless, the conventional ones were not so. Therefore, In this paper, the fuzzy inference technique of PI gains using MMGM(Min Max Gravity Method) which is very similar to humans inference procedures, was presented and allied to the SVC system. The system dynamic responses are examined after applying all small disturbance condition.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2283-2285
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• 2001

This paper proposed to a neural network based fuzzy control (neuro-fuzzy control) technique for attitude control of helicopter with strongly dynamic nonlinearities and derived a helicopter aerodynamic torque equation of helicopter and the force balance equation. A neuro-fuzzy system is a feedforward network that employs a back-propagation algorithm for learning purpose. A neuro-fuzzy system is used to identify nonlinear dynamic systems. Hence, this paper presents methods for the design of a neural network(NN) based fuzzy controller(that is, neuro-fuzzy control) for a helicopter of nonlinear MIMO systems. The proposed neuro-fuzzy control determined to a input-output membership function in fuzzy control and neural networks constructed to improve through learning of input-output membership functions determined in fuzzy control.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.123-126
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• 2000

An elevator system which is a essential equipment for a vertical movement of object, as a property of building, have been drove by various expenditure and purpose. Since developing electrical control technology, control systems are highly developed. An elevator equipment is expended to wide, but a data accuracy acquisition technique and safety predict technique for securing system safety is still basic level. So, objective verification for elevator confidence condition is required absolutely accuracy measurement technique. Therefore, this study is accomplished in order to conquer a method of depending on sense of a manager with a simple numeric measurement data, and construct a logical, analytical foresight system for more efficient elevator management system.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.922-927
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• 1991

This study is aimed to investigate a design problem of the fuzzy logic controller for the activated sludge process(ASP) in sewage treatment. The modeling technique proposed by Sugeno is used to express the ASP effectively and identification of a fuzzy model of the ASP is carried out utilizing actual operational data obtained from a metropolitan sewage plants. The model-based fuzzy controller is designed by rules generated from the identified ASP fuzzy model. Feasibility of the designed controller is tested through computer simulations.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.9
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• pp.417-423
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• 2001

This paper proposes a technique for fault detection and classification for both LIF(Low Impedance Fault)s and HIF(High Impedance Fault)s using Adaptive Network-based Fuzzy Inference System(ANFIS). The inputs into ANFIS are current signals only based on Root-Mean-Square(RMS) values of 3-phase currents and zero sequence current. The performance of the proposed technique is tested on a typical 154 kV Korean transmission line system under various fault conditions. Test results show that the ANFIS can detect and classily faults including (LIFs and HIFs) accurately within half a cycle.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.3
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• pp.231-240
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• 2001

Conventional expert systems has been criticized due to its lack of capability to adapt to the changing decision-making environments. In literature, many methods have been proposed to make expert systems more environment-adaptive by incorporating fuzzy logic and neural networks. The objective of this paper is to propose a new approach to building a self-evolving expert system inference mechanism by integrating fuzzy neural network and fuzzy rule extraction technique. The main recipe of our proposed approach is to fuzzify the training data, train them by a fuzzy neural network, extract a set of fuzzy rules from the trained network, organize a knowledge base, and refine the fuzzy rules by applying a pruning algorithm when the decision-making environments are detected to be changed significantly. To prove the validity, we tested our proposed self-evolving expert systems inference mechanism by using the bankruptcy data, and compared its results with the conventional neural network. Non-parametric statistical analysis of the experimental results showed that our proposed approach is valid significantly.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.83-85
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• 1997

In this paper, a self-tunning fuzzy inference technique for stabilization of the inverted pendulum system is proposed. The facility of this self-tunning fuzzy controller which has swing-up control mode and a stabilization one, moves a pendulum in an initial natural stable equilibrium point and a cart in arbitrary position, to an unstable equilibrium point and a center of rail. Specially, the virtual equilibrium point(${\phi}_{VEq}$) which describes functionally considers the interactive dynamics between a position of cart and a angle of inverted pendulum is introduced. And comparing with the convention optimal controller, the proposed self-tunning fuzzy inference structure made substantially the inverted pendulum system robust and stable.