• 한국생물공학회:학술대회논문집
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• 2000.04a
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• pp.133-136
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• 2000

In recent years, hybrid neural network approaches which combine neural networks and mechanistic models have been gaining considerable interests. These approaches are potentially very efficient to obtain more accurate predictions of process dynamics by combining mechanistic and neural models in such a way that the neural network model properly captures unknown and nonlinear parts of the mechanistic model. In this work, such an approach was applied in the modeling of a full-scale coke wastewater treatment process. First, a simplified mechanistic model was developed based on the Activated Sludge Model No.1 and the specific process knowledge, Then neural network was incorporated with the mechanistic model to compensate the errors between the mechanistic model and the process data. Simulation and actual process data showed that the hybrid modeling approach could predict accurate process dynamics of industrial wastewater treatment plant. The promising results indicated that the hybrid modeling approach could be a useful tool for accurate and cost-effective modeling of biochemical processes.

• Journal of Aerospace System Engineering
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• v.1 no.2
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• pp.37-42
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• 2007

This paper proposes a numerical modeling approach to simulate the hybrid combustion phenomena. From the physical understandings of hybrid combustion, the computational domain was separated into three regions: the solid fuel, gas phase reactive flow, and the interface between solid and fluid. Moreover, for the accurate calculation, computational grids for these regions was generated at every time step considering the instantaneous moving interface which are governed by the balance equations using thermal pyrolysis. In the domain of reactive flow, by virtue of diffusion flame structure, turbulent combustion modeling was introduced using either mixture fraction approach or mean reaction rate approach.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.3
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• pp.43-53
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• 2007

Internet becomes more and more popular, and most companies and institutes use web services for e-business and many other purposes. With the explosion of Internet, the occurrence of cyber terrorism has grown very rapidly. Simulation is one of the most widely used method to study internet worms. But, it is quite challenging to simulate very large-scale worm attacks because of various reasons. In this paper, we propose a hybrid modeling method for RCS(Random Constant Spreading) worm simulation. The proposed hybrid model simulates worm attacks by synchronizing modeling network and packet network. So, this model will be both detailed enough to generate realistic packet traffic, and efficient enough to model a worm spreading through the Internet. Moreover, our model have the capability of dynamic updates of the modeling parameters. Finally, we simulate the hybrid model with the CodeRed worm to show validity of our proposed model for RCS worm simulation.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.269-278
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• 2006

This paper presents the new hybrid data mining technique using error pattern, modeling of improving classification accuracy. The proposed method improves classification accuracy by combining two different supervised learning methods. The main algorithm generates error pattern modeling between the two supervised learning methods(ex: Neural Networks, Decision Tree, Logistic Regression and so on.) The Proposed modeling method has been applied to the simulation of 10,000 data sets generated by Normal and exponential random distribution. The simulation results show that the performance of proposed method is superior to the existing methods like Logistic regression and Discriminant analysis.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11a
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• pp.331.2-331
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• 2002

A modeling method for cantilever beams undergoing axially oscillating motion is presented in this paper. Hybrid deformation variables are employed for the modeling method. Frequency response characteristics are investigated with the modeling method. It is shown that the geometric nonlinear effects of stretching and curvature play important roles to accurately predict the dynamic response. (omitted)

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.3
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• pp.179-182
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• 2003

Component-based method for load model not only should include the performances of the load components, but also should take into consideration the core losses of transformers, the line losses and the capacitor banks. Especially, capacitor bank affects the accuracy of reactive load model in load modeling. But it is difficult to identify actual reactive powers of capacitor banks in power system for load modeling. This research improves the component-based modeling method including uncertain capacitor bank. The proposed method is hybrid technique, which adds the measurement-based method to the existing component-based method for reliable information of capacitor band. The results of case studies were presented to verify the validity of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.12
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• pp.1014-1022
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• 2002

An objective of Automated Highway Systems (AHS) is to increase the safety and throughput of the existing highway infrastructure by introducing traffic automation. AHS is an example of a large scale, multiagent complex dynamical system and is ideally suited for a hierarchical hybrid controller. We discuss a design issue of efficient hybrid controllers for the platoon maneuvers on AHS. For the modeling of a hybrid system including the merge and split operations, a safety distance policy is introduced for the merge and split operations. After that, the platoon system will be modeled by a hybrid system In addition, a hybrid controller for the proposed merge and split operation models is presented. Finally, the performance of the proposed hybrid control scheme is demonstrated via scenarios for platoon maneuvers.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.6
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• pp.294-300
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• 1999

There is a growing interest in hybrid electric vehicles due to environmental concerns. Recent efforts are directed toward developing an improved main component systems for the hybrid electric vehicle applications. Soon after the introduction of electric starter for internal combustion engine early this century, despite being energy efficient and nonpolluting, electric vehicle lost the battle completly to internal combustion engine due to its limited range and inferior performance. Hybrid Electric vehicles offer the most promising solutions to reduce the emission of vehicles. This paper describes a method for cost reduction estimation of parallel hybrid electric vehicle. We used a cost reduction structure that consisted of five major subsystems (three-type and two-type motor) for parallel hybrid electric vehicle. Especially, we estimated the potential for cost reductions in parallel hybrid electric vehicle as a function of time using the learning curve. Also, we estimated the potentials of cost by depreciation.

• 유체기계공업학회:학술대회논문집
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• 2006.08a
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• pp.245-248
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• 2006

Hybrid propulsion systems provide many advantages in terms of stable operation and safety. However, classical hybrid rocket motors have lower fuel regression rate and combustion efficiency compared to solid propellant rocket motor. Accordingly, the recent research efforts are focused on the improvement of engine efficiency and regression rate in the hybrid rocket engine. The present study has numerically investigated the combustion processes in the hybrid rocket engine. The turbulent combustion is represented by the flamelet model and Low Reynolds number $k-{\varepsilon}$ turbulent model is employed to reduce the uncertainties for convective heat transfer near solid fuel surface having strong blowing effect. Based on numerical results, the detailed discussions have been made for the effects of oxygen injection methods and oxygen injection flow rate on flame structure and regression rate in the vortex hybrid rocket engines

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2005.04a
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• pp.201-208
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• 2005

Neuro-Fuzzy modeling approach is proposed to predict the dynamic behavior of a single-degree-of-freedom structure that is equipped with hybrid base isolation system. Hybrid base isolation system consists of friction pendulum systems (FPS) and a magnetorheological (MR) damper. Fuzzy model of the M damper is trained by ANFIS using various displacement, velocity, and voltage combinations that are obtained from a series of performance tests. Modelling of the FPS is carried out with a nonlinear analytical equation that is derived in this study and neuro-fuzzy training. Fuzzy logic controller is employed to control the command voltage that is sent to MR damper. The dynamic responses or experimental structure subjected to various earthquake excitations are compared with numerically simulated results using neuro-fuzzy modeling method. Numerical simulation using neuro-fuzzy models of the MR damper and FPS predict response of the hybrid base isolation system very well.