• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.4
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• pp.1-11
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• 2014

This paper addresses the emotion computing model for software affective agents. In this paper, emotion is represented in valence-arousal-dominance dimensions instead of discrete categorical representation approach. Firstly, a novel emotion model architecture for affective agents is proposed based on Scherer's componential theories of human emotion, which is one of the well-known emotion models in psychological area. Then a fuzzy logic is applied to determine emotional statuses in the emotion model architecture, i.e., the first valence and arousal, the second valence and arousal, and dominance. The proposed methods are implemented and tested by applying them in a virtual training system for children's neurobehavioral disorders.

• Proceedings of the IEEK Conference
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• summer
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• pp.119-121
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• 2004

Video event detection has become an essential application in multimedia computing. For sports video, salient events are usually detected by analyzing video sequence by specific decision rules. However in many kinds of sports video (e.g. soccer), the game contains continuous actions, in which the boundaries of shots, scenes are uncertain. So the conventional analyzing methods using crisp decisions are not efficient. Fuzzy logic is a natural approach that can tackle this problem. In this paper, we present a new approach using fuzzy technique for event detection in soccer video. The experiment shows encouraging results for this method

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1370-1373
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• 1993

In controlling a system having many variables to control and multi objectives to satisfy such as a roof crane system, it is often difficult to obtain fuzzy If-Then rules in usual ways. As an alternative, we can more easely obtain rules in such a manner that we obtain each independent group of rules using partial variables for a partial objective. In this case, obtained rules can be conflicting with each other and conventional inference methods cannot handle such rules effectively. In this paper, we propose a roof crane controller with optimal velocity profile generator and a fuzzy logic controller with an inference method suitable for such conflicting rules.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.444-451
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• 1999

A diagnostic rule-base design method for enhancing fault detection and isolation performance of multiple obsever based fault detection isolation schemes (FIDS) is presented. The diagnostic rule-base has a hierarchical framework to perform detection and isolation of faults of interest, and diagnosis of process faults. The decision unit comprises a rule base and a fuzzy inference engine and removes some difficulties of conventional decision unit which includes crisp logic with threshold values. Emphasis is placed on the design and evaluation methods of the diagnostic rult-base. The suggested scheme is applied to the FDIS design for a DC motor driven centrifugal pump system.

• The Journal of Information Technology and Database
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• v.7 no.1
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• pp.42-53
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• 2000

The major goal of this research is to develop an optimal route search algorithm for an intelligent route guidance system, one sub-area of ITS. ITS stands for intelligent Transportation System. ITS offers a fundamental solution to various issues concerning transportation and it will eventually help comfortable and swift moves of drivers by receiving and transmitting information on humans, roads and automobiles. Genetic algorithm, and fuzzy logic are utilized in order to implement the proposed algorithm. Using genetic algorithm, the proposed algorithm searches shortest routes in terms of travel time in consideration of stochastic traffic volume, diverse turn constraints, etc. Then using fuzzy logic, it selects driver-preference optimal route among the candidate routes searched by GA, taking into account various driver's preferences such as difficulty degree of driving and surrounding scenery of road, etc. In order to evaluate this algorithm, a virtual road-traffic network DB with various road attributes is simulated, where the suggested algorithm promptly produces the best route for a driver with reference to his or her preferences.

• Proceedings of the KIEE Conference
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• 2005.10c
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• pp.114-117
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• 2005

Auto Steering System is the device for course keeping or course altering to ship's steering system. The Purpose of automatic steering system is to keep the ship's course stable with the minimum course and rudder angle. Recently, modern control theories are being used widely in analyzing and designing the ship system. Though P.D type auto pilots are widely used in ships, the stability and the adjusting methods are not clarified. In this paper the authors proposed auto steering system with Fuzzy Logic Controller. In the fuzzy control the things that the actual operators of a steering wheel has acquired through their experience can be logically described by the Lingustic Control Rule. The characteristic of the control system were investigated through the computer simulation results. it was found that the fuzzy logic control was more efficient than the conventional system.

• Steel and Composite Structures
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• v.48 no.5
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• pp.499-505
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• 2023

Geological hazards in landslide is one of the most extensive and destructive phenomena are among natural disasters. According to the topography high mountains, tectonic activity, high seismicity, diverse conditions Geology and climate, basically China to create a wide spectrum of landslides have natural conditions and these landslides are annual. They cause a lot of financial losses to the country. It is very difficult to predict the time of the landslide, hence the identification landslide sensitive areas and zoning of these areas based on the potential risk is very important. Therefore, it should be susceptible areas landslides should be identified in order to reduce damages caused by landslides find. the main purpose of landslide sensitivity analysis is identification high-risk areas and as a result, reducing damages caused by landslides It is the way of appropriate actions.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2296-2298
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• 2000

Fuzzy control has been researched for application of industrial processes which have no accurate mathematical model and could not controlled by conventional methods because of a lack of quantitative input-output data. Intelligent control approach based on fuzzy logic could directly reflex human thinking and natural language to controller comparing with conventional methods. In this paper, fuzzy controller is implemented to acquire operator's knowledge. The tested system is constructed for sending a ball to the goal position using wind from two DC motors in the path. This system contains non-linearity and uncertainty because of the characteristic of aerodynamics inside the path. Ball position is measured by a vision camera. The system used in this experiment could be hardly modeled by mathematic methods and could not be easily controlled by linear control manners. The controller, in this paper is designed based on the input-output data and experimental knowledge obtained by trials.

• 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.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2170-2178
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• 2015

This paper presents the effective and reliable speed control of PMDC motors under variable loads and reference speeds. As is known DC motors are more preferred in industrial practices. This is that, the PMDC motors don’t require brush and commutator care and to increase in torque per motor depending on developments in power electronics. In this study, proportional-integral controller (PI) and fuzzy logic controller (FL) have been designed for speed control of PMDC motor. In the design of these controllers, characteristics such as minimum overrun time, response time to the load, settling time and ideal rise time have been taken into consideration for better stability performance. In this design, the best system response was searched by examining the effect of different defuzzification methods onto the fuzzy logic system response. In conclusion, it has been seen that FL controller has a better performance for variable speed-load control of PMDC motor compared to PI controller.