• Transactions of Materials Processing
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• v.8 no.4
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• pp.331-339
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• 1999

In this study, to analyze the shaped drawing process from round bar, the practical conical die with considering die radius and bearing was defined by a mathematical expression, and also a simple technique for initial mesh generation to the shaped drawing process was proposed. The drawing of rectangular section from round bar, one of the shaped drawing process, has been simulated by using non-steady state 3D rigid plastic finite element method in order to evaluate the influence of semi-die angle and reduction in area to corner filling. Other process variables such as friction constant, rectangular ratio, die radius and bearing length were fixed during the simulation. An artificial neural network has been introduced to obtain the optimal process conditions which gave rise to a fast simulation.

• Journal of computational fluids engineering
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• v.6 no.2
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• pp.47-55
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• 2001

In recent years cluster systems using off-the-shelf processors and networks components have been increasing popular. Since actual performance of a cluster system varies significantly for different architectures, representative in-house codes from major application fields were executed to evaluate the actual performance of systems with different combination of CPU, network, and network topology. As an example of practical CFD(Computational Fluid Dynamics) simulations, the flow past an Onera-M6 wing and the flow past an infinite wing were simulated on clusters of Linux and several other hardware environments.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.339-343
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• 2005

Boolean networks(BN) construction is one of the commonly used methods for building gene networks from time series microarray data. However, BN has two major drawbacks. First, it requires heavy computing times. Second, the binary transformation of the microarray data may cause a loss of information. This paper propose two methods using liner regression to construct gene regulatory networks. The first proposed method uses regression based BN variable selection method, which reduces the computing time significantly in the BN construction. The second method is the regression based network method that can flexibly incorporate the interaction of the genes using continuous gene expression data. We construct the network structure from the simulated data to compare the computing times between Boolean networks and the proposed method. The regression based network method is evaluated using a microarray data of cell cycle in Caulobacter crescentus.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.894-897
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• 1995

This paper focuses on self-organization of fuzzy rules for performance management of computer communication networks serving manufacturing systems. The performance management aims to improve the network performance in handling various types of messages by on-line adjustment of protocol parameters. The principle of fuzzy logic has been used in representing the knowledge of human expert on the performance management and in deriving management decisions. In this paper, we present applications of genetic algorithm, simulated annealing, and evolution strategies to find a better set of rules for various network conditions. The efficacy of this self-organization is demonstrated by discrete simulation of an IEEE 802.4 network.

• Transactions of the Korean Society of Automotive Engineers
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• v.15 no.2
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• pp.35-40
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• 2007

The gaseous fuel injection (GFI) type in LPG fuel supply system has more advantage than the liquified fuel injection type from the viewpoint of durability and cost reduction. But in GFI system, to control pressure and temperature of gaseous fuel is needed to get precision fuel metering for the compressible characteristic of gaseous fuel. In this study, the effects of pressure and temperature on the fuel metering was simulated by commercial flow network analysis package, Flowmaster. And the fuel composition effects on the fuel metering were also studied to figure out the fuel metering characteristics.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.535-536
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• 2006

This paper reports investigation into the factors that influence the transient behavior of the wind power generation system following network fault conditions. It is shown that the critical clearing time(CCT) can be affected by various factors contributed by the host network. Such factors include capacity of wind power, power factor, the length of the interfacing line, etc. This investigation is conducted en a simulated grid-connected wind farm using Digsilent Power Factory.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.426-429
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• 2000

In this paper, we propose a system identification and control method using bias-modified neural network. The proposed method performs, for a nonlinear plant with unknown functions, system identification using bias-modified neural network, and then controller is designed with those identified informations. In order to verify the usefulness of the proposed method, we simulated the proposed control method with one link manipulator system and confirmed the excellency.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12A
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• pp.1285-1290
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• 2004

In this paper, a new algorithm for contention resolution in optical burst switched network is proposed and simulated. The proposed algorithm is made from the all mixing of wavelength conversion, deflection routing, segmentation, and optical fiber delay line buffering. We analysis the performance of the proposed contention resolution algorithm by using ns-2. The application of the algorithm into Korea backbone network shows the superior performance of a low burst loss probability.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1440-1443
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• 1999

This paper proposes fault detection method using a neural network & fuzzy logic on distribution lines. Fault on distribution lines is simulated using EMTP. The pattern of high impedance fault on pebbles, ground and short-circuit fault were take as the learning model. In this paper proposed fault detection method is evaluated on various conditions. The average values after analyzing fault current by FFT of even odd harmonics and fundamental rms were used for the neural network input. Test results were verified the validity of the proposed method

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.1-6
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• 1990

Neural network is a computational model of ft biological nervous system developed ID exploit its intelligence and parallelism. Applying neural networks so robots creates many advantages over conventional control methods such as learning, real-time control, and continuous performance improvement through training and adaptation. In this paper, dynamic control of a six-link robot will be presented using neural networks. The neural network model used in this paper is the backpropagation network. Simulated control of the PUMA 560 am shows that it can move a high speed as well as adapt to unforseen load changes and sensor noise. The results are compared with the conventional PD control scheme.