• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.66-71
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• 2003

In the past, when there were few vehicles on the road, the T.O.D.(Time of Day) traffic signal worked very well. The T.O.D. signal operates on a preset signal cycling which cycles on the basis of the average number of average passenger cars in the memory device of an electric signal unit. Today, with increasing traffic and congested roads, the conventional traffic light creates startup-delay time and end lag time so that thirty to forty-five percent efficiency in traffic handling is lost, as well as adding to fuel costs. To solve this problem, this paper proposes a new concept of optimal green time algorithm, which reduces average vehicle waiting time while improving average vehicle speed using fuzzy rules and neural networks. Through computer simulation, this method has been proven to be much more efficient than fixed time interval signals. Fuzzy Neural Network will consistanly improve average waiting time, vehicle speed, and fuel consumption.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.105-111
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• 2003

This paper is researching the storing of 40 different kinds of conditions. Such as, car speed, delay in starting time and the volume of cars in traffic. Through the use of a central nervous networking system or AI, using 10 different intersecting roads. We will improve the green traffic light. And allow more cars to easily flow through the intersections. Now days, with increasing many vehicles on restricted roads, the conventional traffic light creates prove startup-delay time and end-lag-time. The conventional traffic light loses the function of optimal cycle. And so, 30-45% of conventional traffic cycle is not matched to the present traffic cycle. In this paper proposes electro sensitive traffic light using fuzzy look up table method which will reduce the average vehicle waiting time and improve average vehicle speed. Computer simulation results prove that reducing the average vehicle waiting time which proposed considering passing vehicle length for optimal traffic cycle is better than fixed signal method which dosen't consider vehicle length.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권4호
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• pp.360-366
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• 2005

In the past, when there were few vehicles on the road, the T.O.D.(Time of Day) traffic signal worked very well. The T.O.D. signal operates on a preset signal cycling which cycles on the basis of the average number of average passenger cars in the memory device of an electric signal unit. Now days, with increasing many vehicles on restricted roads, the conventional traffic light creates startup-delay time and end-lag-time. The conventional traffic light loses the function of optimal cycle. And so, $30-45\%$ of conventional traffic cycle is not matched to the present traffic cycle. In this paper we proposes electro sensitive traffic light using fuzzy look up table method which will reduce the average vehicle waiting time and improve average vehicle speed. Computer simulation results prove that reducing the average vehicle waiting time which proposed considering passing vehicle length for optimal traffic cycle is better than fixed signal method which doesn't consider vehicle length.

• 한국지능시스템학회논문지
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• 제10권4호
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• pp.330-337
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• 2000

본 논문은 10개 교차로를 연동제어를 할 수 있는 새로운 교통체제 개념을 제안한다. 예를 들어서 오늘 야구경기가 8시경에 열린다고 하면 야구경기가 시작하기 전 1 시간 혹은 1시간 혹은 1시간 30분전에 교통량이 증가할 것이다. 이럴 때에는 아무리 우수한 전자 신호등 시스템도 최적녹색시간을 예측할 수 없다. 그러므로, 본 논문에서는 평균 승용차 대기시간을 최소화하고 평균 주행속도를 향상하기 위해서 퍼지규칙 및 신경망을 이용한다. 모의실험결과 제안된 연동 녹색시간이 연동 녹색 시간을 고려하지 않은 전자신호등보다 평균 승용차 대기시간을 줄일 수 있음을 입증했다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 춘계학술대회 학술발표 논문집 제15권 제1호
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• pp.161-165
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• 2005

최적 교통 주기를 산출하기 위해서는 하위교차로에 대기차량이 얼마나 있는지를 점검해야 한다. 왜냐하면 대기차량이 상위교차로의 길이보다 크면 출발 지연 시간 및 승용차 대기시간이 발생하기 때문이다. 승용차 대기시간을 단축시키기 위해서 본 논문에서는 퍼지 신경망을 이용한 최적 연동 녹색시간 알고리즘을 제안한다. 컴퓨터 모의실험을 통해서, 서로 다른 교차로 조건을 고려하지 않은 고정 교통신호등 보다 평균 주행속도가 향상 된 것을 입증하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.591-595
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• 1998

This paper proposes a new concept of optimal shortest path algorithm which reduce average vehicle wating time and improve average vehicle speed, Electro sensitive traffic system can extend the traffic cycle when three are many vehicles on the road or it can reduce the traffic cycle when there are small vehicles on the road. But electro sensitive traffic light system doesn't control that kind of function when the average vehicle speed is 10km -20km. Therefore, in this paper to reduce vehicle waiting time we developed design of traffic cycle software tool that can arrive destinination as soon as possible using optimal shortest pass algorithm. Computer simulation result proved 10%-32% reducing average vehicle wating time and average vehicle speed which can select shortest route using built in G.P.S. vehicle is better than not being able to select shortest route function.

• 제어로봇시스템학회논문지
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• 제6권3호
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• pp.273-283
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• 2000

In this paper we suggest an optimal design method of Fuzzy-Neural Networks(FNN) model for complex and nonlinear systems. The FNNs use the simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM(Hard C-Means) Clustering Algorithm to find initial parameters of the membership function. The parameters such as parameters of membership functions learning rates and momentum weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. According to selection and adjustment of a weighting factor of an aggregate objective function which depends on the number of data and a certain degree of nonlinearity (distribution of I/O data we show that it is available and effective to design and optimal FNN model structure with a mutual balance and dependency between approximation and generalization abilities. This methodology sheds light on the role and impact of different parameters of the model on its performance (especially the mapping and predicting capabilities of the rule based computing). To evaluate the performance of the proposed model we use the time series data for gas furnace the data of sewage treatment process and traffic route choice process.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.292-297
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• 2000

본 논문은 10개 교차로를 연동제어를 할 수 있는 새로운 교통체제 개념을 제안한다. 예를 들어서 오늘 야구경기가 8시경에 열린다고 하면 야구경기가 열리기전 1시간 흑은 1시간 30분전에 교통량이 증가할 것이다. 이럴때에는 아무리 우수한 전자 신호등 시스템도 최적녹색시간을 예측 할 수 없다. 그러므로, 본 논문에서는 평균 승용차 대기시간을 최소화하고 평균 주행속도를 향상하기 위해서 퍼지규칙 및 신경망을 이용한다. 모의실험결과 제안된 연동 녹색시간이 연동 녹색시간을 고려하지 않은 전자신호등보다 평균 승용차 대기시간을 줄일 수 있음을 입증했다.

• 전자공학회논문지CI
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• 제41권4호
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• pp.73-83
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• 2004

제한된 도로에서 증가되는 차량으로 인해서, 평균주행속도가 떨어지고 교차로의 대기 손실이 많아지고 있다. 본 논문은 10개 교차로를 연동 제어를 할 수 있는 새로운 교통체제 개념을 제안한다. 예를 들어서 오늘 야구경기가 8시경에 열린다고 하면 야구경기가 시작하기 전 1시간 혹은 1시간 30분전에 교통량이 증가할 것이다. 이럴 때에는 아무리 우수한 전자 신호등 시스템도 최적녹색시간을 예측할 수 없다. 그러므로 본 논문에서는 평균 승용차 대기시간을 최소화하고 평균 주행속도를 향상하기 위해서 전처리로써 퍼지규칙 및 신경망을 이용한다. 또한 후처리로써 예기치 못한 상황을 지능적으로 제어할 수 있는 지능적인 소프트웨어 PLC(Programmable Logic Controller)를 구현하였다. 시뮬레이션결과 제안된 연동 녹색시간이 연동 녹색시간을 고려하지 않은 전자신호등보다 평균 승용차 대기시간을 줄일 수 있음을 입증했다.