• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.33-42
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• 1995

A practical application of a fuzzy-neuro controller is described for an air-conditioning system. Air-handing units are being widely used for improving the performance of central air-conditioning systems. The fuzzy-neuro control system has two controlled variables, temperature and humidity and three control elements, cooling, heating, and humidification. In order to achieve high efficiency and economical contorl, especially in large offices and industrial buildings, two controllable parameters, temperature and humidity, must be adequately controlled by the three final controlling elements. In this paper a fuzzy-neuro control system is described for controlling air-conditioning systems efficiently and economically. Simulation results confirmed that the fuzzy neuro control system is effective for this multivariable system.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2470-2472
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• 2001

This paper describes the application of a fuzzy-tuning PID controller to a 3-DOF attitude control of a small model helicopter in hover for the compensation of coupling effects between each axis and system uncertainties due to the variation of engine RPM. A Low-level PID controller is designed by Ziegler-Nichols method and its gains are tuned by a high-level fuzzy system based on error states and its time derivatives. The experimental results show that the attitude control performance of fuzzy-tuning PID controller is improved comparing with that of a Ziegler-Nichols PID controller and fuzzy controller.

• Proceedings of the KIEE Conference
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• 2002.06a
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• pp.60-63
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• 2002

This paper presents a control approach for designing a self tuning fuzzy controller for SVC system, A SVC constructed by a Fixed Capacitor and a Thyristor Controlled Reactor is designed and implemented to improve the damping of a synchronous generator, as well as controlling the system voltage, The proposed parameter self tuning algorithm of fuzzy controller is based on the steepest decent method using two direction vectors which make error between inference values of fuzzy controller and output values of the specially selected PSS reduce steepestly, The related simulation results show that the proposed fuzzy controller is more powerful than the conventional ones.

• Journal of Power Electronics
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• v.7 no.3
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• pp.238-245
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• 2007

This paper considers the problem of regulating the output voltage of a current doubler rectified asymmetric half-bridge (CDRAHB) DC/DC converter via fuzzy integral control. First, we model the dynamic characteristics of the CDRAHB converter with the state-space averaging method, and after introducing an additional integral state of the output regulation error, we obtain the Takagi-Sugeno (TS) fuzzy model for the augmented system. Second, the concept of parallel distributed compensation is applied to the design of the TS fuzzy integral controller, in which the state feedback gains are obtained by solving the linear matrix inequalities (LMIs). Finally, numerical simulations of the considered design method are compared to those of the conventional method, in which a compensated error amplifier is designed for the stability of the feedback control loop.

• 한국정보통신설비학회:학술대회논문집
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• 2008.08a
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• pp.177-180
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• 2008

There are many application areas of sensor networks, such as surveillance, hospital monitoring, and home network. These are dependent on the secure operation of networks, and will have serious outcome if the networks is injured. An adversary can inject false data into the network through the compromising node. Ye et al. proposed a statistical en-route filtering scheme (SEF) to detect such false data during forwarding process. In this scheme, it is important that the choice of the threshold value since it trades off security and overhead. This paper presents an adaptive threshold value determining method in the SEF using fuzzy logic. The fuzzy logic determines a security distance value by considering the situation of the network. The Sensor network is divided into several areas by the security distance value, it can each area to uses the different threshold value. The fuzzy based threshold value can reduce the energy consumption in transmitting.

• Journal of the military operations research society of Korea
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• v.18 no.1
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• pp.47-60
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• 1992

A class of allocation problems can be modeled in a linear programming formulation. But in reality, the coefficient of both the cost and constraint equations can not be generally determined by crisp numbers due to the imprecision or fuzziness in the related parameters. To account for this. a fuzzy version is considered and solved by transforming to a conventional non-linear programming model. This gives a solution as well as the degree that the solution satisfies the objective and constraints simultaneously and hence will be very useful to a decision maker. An attacker assignment problem for multiple fired targets has been modeled by a linear programming formulation by Lemus and David. in which the objective is to minimize the cost that might occur on attacker's losses during the mission. A fuzzy version of the model is formulated and solved by transforming it to a conventional nonlinear programming formulation following the Tanaka's approach. It is also expected that the fuzzy approach will have wide applicability in general allocation problems

• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.233-246
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• 2003

This paper presents a methodology to account for the partial or gradual changes of environmental phenomena in categorical map information for the fusion/integration of multiple spatial data. The fuzzy set based spatial data fusion scheme is applied in order to account for the fuzziness of boundaries in categorical information showing the partial or gradual environmental impacts. The fuzziness or uncertainty of boundary is represented as two kinds of fuzzy membership functions based on fuzzy object concept and the effects of them are quantitatively evaluated with the help of a cross validation procedure. A case study for landslide hazard assessment demonstrates the better performance of this scheme as compared to traditional crisp boundary representation.

• Journal of Multimedia Information System
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• v.6 no.2
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• pp.87-90
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• 2019

Machine learning techniques have been applied in almost all the domains of human life to aid and enhance the problem solving capabilities of the system. The field of medical science has improved to a greater extent with the advent and application of these techniques. Efficient expert systems using various soft computing techniques like artificial neural network, Fuzzy Logic, Genetic algorithm, Hybrid system, etc. are being developed to equip medical practitioner with better and effective diagnosing capabilities. In this paper, a comparative study to evaluate the predictive performance of subtractive clustering based ANFIS hybrid system (SCANFIS) with Fuzzy C-Means (FCM) based ANFIS system (FCMANFIS) for Alzheimer disease (AD) has been taken. To evaluate the performance of these two systems, three parameters i.e. root mean square error (RMSE), prediction accuracy and precision are implemented. Experimental results demonstrated that the FCMANFIS model produce better results when compared to SCANFIS model in predictive analysis of Alzheimer disease (AD).

• Nuclear Engineering and Technology
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• v.53 no.5
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• pp.1464-1478
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• 2021

Selective Production of Exotic Species is an innovative plant for advanced nuclear physic studies. A radioactive beam, generated by using an UCx target-ion source system, is ionized, selected and accelerated for experimental objects. Very high vacuum conditions and appropriate safety systems to storage exhaust gases are required to avoid radiological risk for operators and people. In this paper, Failure Mode, Effects, and Criticality Analysis of a preliminary design of high activity gas recovery system is performed by using a modified Fuzzy Risk Priority Number to rank the most critical components in terms of failures and human errors. Comparisons between fuzzy approach and classic application allow to show that Fuzzy Risk Priority Number is able to enhance the focus of risk assessments and to improve the safety of complex and innovative systems such as those under consideration.

• Journal of Digital Contents Society
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• v.9 no.1
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• pp.53-60
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• 2008

Based on similarities between fuzzy set theory and mathematical morphology, Grabish proposed a fuzzy morphology based on the Sugeno fuzzy integral. This paper proposes a fuzzy mathematical morphology based on the defuzzification of the fuzzy measure which corresponds to fuzzy integral. Its process makes a fuzzy set used as a measure of the inclusion of each fuzzy measure for subsets. To calculate such an integral a $\lambda$-fuzzy measure is defined which gives every subsets associated with the universe of discourse, a definite non-negative weight. Fast implementable definitions for erosion and dilation based on the fuzzy measure was given. An application for robust skeletonization of two-dimensional objects was presented. Simulation examples showed that the object reconstruction from their skeletal subsets that can be achieved by using the proposed was better than by using the binary mathematical morphology in most cases.