• 한국경영과학회지
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• 제25권3호
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• pp.81-89
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• 2000

The real-time multicast problem is to construct a multicast tree starting from a source node and including multiple destination nodes and that has minimum network cost with delay constraints. It is known that to find a tree of the minimum network cost is the Steiner Tree problem which is NP-complete. In this paper, we propose a genetic algorithm to solve the multicast tree with minimum network cost and the delay constraints. The computational results obtained by comparing an existing algorithm. Kompella algorithm, and the proposed algorithm show that our algorithm tends to find lower network cost on the average than Kompella algorithm does.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2001년도 학술발표회 발표논문집
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• pp.59-64
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• 2001

The objectives of the thesis are to propose a pattern classification method for remote sensing data using artificial neural network. First, we apply the error back propagation algorithm to classify the remote sensing data. In this case, the classification performance depends on a training data set. Using the training data set and the error back propagation algorithm, a layered neural network is trained such that the training pattern are classified with a specified accuracy. After training the neural network, some pixels are deleted from the original training data set if they are incorrectly classified and a new training data set is built up. Once training is complete, a testing data set is classified by using the trained neural network. The classification results of Landsat TM data show that this approach produces excellent results which are more realistic and noiseless compared with a conventional Bayesian method.

• 한국유체기계학회 논문집
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• 제13권3호
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• pp.54-58
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• 2010

The pneumatic waste collection system, which is a complete solution for solving the waste collection problems, are constructed in many countries all over the world. However, research data for piping network design are insufficient. In this paper the pressure losses of the straight and curved pipes, pipe junctions are obtained using the numerical method in order to investigate the optimal pipe network design for the waste collection system. As an experimental result, the length of 1.8 meter is the reasonable for the radius of curvature of a curved pipe and the angle of 30 degree is suitable for confluent pipe.

• 신재생에너지
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• 제4권4호
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• pp.23-29
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• 2008

Wind farm development project contains high business risks because that a wind farm, which is to be operating for 20 years, has to be designed and assessed only relying on a year or little more in-situ wind data. Accordingly, long-term correction of short-term measurement data is one of most important process in wind resource assessment for project feasibility investigation. This paper shows comparison of general Measure-Correlate-Prediction models and neural network, and presents new method using neural network for increasing prediction accuracy by accommodating multiple reference data. The proposed method would be interim step to complete long-term correction methodology for Korea, complicated Monsoon country where seasonal and diurnal variation of local meteorology is very wide.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2010년도 춘계학술대회 논문집
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• pp.1589-1595
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• 2010

China has experienced rapid economic growth and burgeoning trade since it began economic reforms and an opening policy. With this the amount of marine cargoes between Korea and China had been increased Recently this increasing rate of cargoes, the development of the Yellow Sea Sub-Region and the change of the Northeast Asian logistics network have acted as important factors of Korea's strategy to be the Northeast Asian logistics hub. This paper analyzes China's inland transport network to offer basic understanding on transport and logistics network in China. Therefore, the outcomes of this paper could be used as basic materials to further transport and logistics cooperation between China and Korea and to developing a more realistic plan to complete Korea's Northeast Asia logistics hub strategy.

• 한국통신학회논문지
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• 제24권12A호
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• pp.1985-1991
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• 1999

본 논문은 HANbit ACE64 ATM 교환기 시스템의 데이터 경로인 IMI(Inter Module Path)에 사용되는 고속 전송선로인 Twinax 케이블을 two-port lumped Spice-network 모델로 구현하기 위해 lumped 네트워크 요소와 수학적 함수를 사용하여 개발하였다. 사용된 요소들은 저항성분과 주파수의존 전압제어 소스로 구성되어 있고 Hspice 수학적 함수인 FREQ, DELAY, POLY를 사용하여 구현하였다. 구현된 모델을 사용하여 케이블 길이와 종류에 따른 각종 노이즈 분석을 실시하여 그 특성을 비교 분석하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
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• pp.285-289
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• 1996

Fuzzy logic controllers have been shown better performance than conventional ones especially in highly nonlinear plants. These results are caused by the nonlinear fuzzy rules were not sufficient to cope with significant uncertainty of the plants and environment. Moreover, it is hard to make fuzzy rules consistent and complete. In this paper, we employed a predictive neural network to enhance the nonlinear inference capability. The predictive neural network generates predictive outputs of a controlled plant using the current and past outputs and current inputs. These predictive outputs are used in terms of fuzzy rules in fuzzy inferencing. From experiments, we found that the predictive term of fuzzy rules enhanced the inference capability of the controller. This predictive neural network can also help the controller cope with uncertainty of plants or environment by on-line learning.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회B
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• pp.2794-2797
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• 2008

The pneumatic waste collection system, which is a complete solution for solving the waste collection problems, are constructed in many countries all over the world. However, research data for piping network design are insufficient. In this paper the pressure losses of the straight and curved pipes, pipe junctions are obtained using the numerical method in order to investigate the optimal pipe network design for the waste collection system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 추계학술대회 논문집 학회본부
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• pp.401-403
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• 1996

In this paper, a new control strategy is presented that combines sliding mode control theory with a neural network. Sliding mode control theory requires the complete knowledge of the dynamics of the controlled system. However, in practice, one often bas only a small number of state measurements. This could be a serious limitation on the practical usefulness of sliding mode control theory. A multilayer neural network is employed to solve this kind of problem. The neural network serves as a compensator without a prior knowledge about the system. The proposed control algorithm is applied to a class of uncertain nonlinear system. The robustness against parameter uncertainty, nonlinearity and external disturbances, and the effectiveness is verified by the simulation results.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1993년도 하계학술대회 논문집 A
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• pp.131-133
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• 1993

In the power system state estimation, the J(x)-index test and normalized residuals $r_N$ have been used to detect the presence of bad measurements and identify their location. But, these methods require the complete re-estimation of system states whenever bad data is identified. This paper presents back-propagation neural network model using autoregressive filter for identification of bad measurements. The performances of neural network method are compared with those of conventional methods and simulation results show the good performance in the bad data identification based on the neural network under sample power system.