• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.65-73
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• 2006

It is very difficult for the teacher to know who understands the lecture or not in the classroom. Therefore, in this paper, it proposed the algorithm of student score evaluation algorithm using full duplex method. Moreover, it confirms that full duplex method using fuzzy rules and neural network can tell where misunderstanding of the problems in the test. The computer simulation results shows that the full duplex virtual learning system has been proven to be much more efficient than one way traditional method which unfortunately does not consider the students understanding.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.233-238
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• 2010

This paper describes a multi-mobile robot system with fuzzy rule based structure in collision avoidance. Collision avoidance is an important function to perform a given task collaboratively and cooperatively in multi-mobile robot environments. So the important but challenging problem is handled in this paper. Considered obstacles for collision avoidance between multi mobile robots are static, dynamic, or both of them at the same time. Using the fuzzy rule based structure, distance and angle from a robot to obstacles are described as fuzzy linguistic values and steering angle for the robot are updated from the collision environments. As a result, the multi-mobile robot can modify a global path from a robot itself to its own target. In addition, avoiding collision with static or dynamic obstacles for the robot system can be achieved. Simulation based experimental results are given to show usefulness of this method.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.956-958
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• 1995

This paper presents the automatic construction of fuzzy rule-based systems for diagnosing the faults of complex systems. Generally, fuzzy systems work well when we can use expert's experience to articulate fuzzy IF-THEN rules and memberships for fuzzy sets. When we cannot do this, we should generate the fuzzy rules and membership functions for fuzzy sets directly from experimental data. In this paper, we propose a new method on how to extract fuzzy sets and fuzzy rules. We also introduce an efficient fine-tunning algorithm of the parameters of membership functions.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.6
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• pp.79-88
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• 1997

New technologies, systems, and services in telecommunication have increased the need for an efficient and robust control mechanism to protect switching systems from overload. To achieve proper control, it is necessary to find a set of parameters that can describe the system. However, it is difficult to find types of data that can form a suitable basis for control. In this paper, we categorize the load status of a switching system into three classes (i.e., normal state, pre-overload state, and overload state) and formulate the overload detection as a classification problem. We find the relationships between the load classes and a set of monitored switching system parameters by applying a fuzzy rule-generation method. The rules are automatically generated from training data. Simulation results involving a switching system is given.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.399-405
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• 2002

Now days, it is based on GIS and GPS, it can search for the shortest path and estimation of arrival time by using the internet and cell phone to driver. But, even though good car navigation system does not create which is the shortest path when there average vehicle speed is 10 -20 Km. Therefore In order to reduce vehicle waiting time and average vehicle speed, we suggest optimal green time algorithm using fuzzy adaptive control , where there are different traffic intersection length and lane. In this paper, it will be able to forecast the optimal traffic Information, estimation of destination arrival time, under construction road, and dangerous road using internet.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.967-969
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• 1996

This paper presents fuzzy control rules for automatically driving a model car. The model car has a two sensors. This sensors measure a road outline and get a distance between a model car and a road outline. A Fuzzy Logic Controller(FLC) bases on a knowledge of the human experience. A FLC designed successfully controls the model car. Simulations results verifies the validity of proposed algorithm.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2546-2548
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• 2003

G-K 클러스터링이 가지는 우수한 클러스터 분류 성능에도 불구하고 데이터의 편중 및 분포 밀도에 의하여 클러스터링의 결과과 만족스럽지 못하는 경우가 발생한다. 제안된 방법에서는, G-K 클러스터링에서 데이터의 분포 및 밀도 등과 같은 다양한 조건에 대한 문제를 동시에 고려함으로써 클러스터링 결과를 개선한다. G-K 클러스터링에서 일부 파라미터의 수동적 파라미터 결정 방법을 Mountain 방법을 이용하여 능동적인 알고리즘으로 대치하여 클러스터 최적화 과정을 더욱 용이하게 한다. 이러한 클러스터링의 장점은 뉴로-퍼지 모델의 규칙 감소와 성능개선으로 나타나며 이를 시뮬레이션을 통하여 보이고자 한다.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.498-500
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• 1993

This paper presents handover algorithm method using fuzzy rules and neura1 network. In future mobile communication systems, the amount of call requests over a region will increase dramatically. This problem has to be solved by decreasing the cell size. But, this method lets a mobile station switch the a base station at a higher rate. In order to maintain better mobile communication system in a micro or pico cellular system, better handover algorithm must be devoloped. In this paper, we propose a handover algorithm which is based on the fuzzy teory that is applied to make rules with the parameters and neural network that is to learn rules. This new handover algorithm is tested by computer simulation and compared with the conventional algorithms.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.304-305
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• 2007

본 논문에서는 진단부분에서 서버를 중심으로 받은 정보를 능동적으로 해석하고 이상 유무에 따른 차단 역할 수행하도록 하는 지능형 차단 시스템에 대한 알고리즘 개발을 목표로 하고 있다. 제안하고자 하는 분류 알고리즘이란, 저압 배선에서 받은 신호에 대한 해석과 더불어 이를 각 이상 정도에 따라 분류하는 것을 말한다. 일반적으로, TFDR을 통해 알아 낼 수 있는 이상 유무의 종류는 damage, open 그리고 short 등이다. 도선 이상의 종류 및 특성에 따른 분류를 위하여, 알고리즘 개발을 위한 사전 이론 조사 및 개요 구성을 목표로 하고 있다. 또한, 기존의 통신 선 상에서 이루어진 결과를 토대로 한 퍼지 분류 규칙 생성 및 분류 알고리즘 개발 역시 앞으로 수행 될 예정이며, 이를 통한 지능형 차단 시스템 구축이 최종 목표이다.

• 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.