• Water for future
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• v.24 no.2
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• pp.81-95
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• 1991

For investigation of the interaction of tide and river flow, the derived equations are solved analytically using the approximation method of perturbation. The convective inertia and nonlinear bottom friction terms are included in the derivations. The harmonic analysis is applied to decompose the complicated interaction of the freshwater discharge with various constituents of tide into its individual interaction with each constituent. In this study, four main constituents(M2, S2, Kl, 01) are included. The relations of dimensionless parameters of the tide, especially the dimensionless damping modulus, are then determined for each solution. The results show that analytical solution of dimensionless damping modulus underestimates the measured value obtained from harmonic analysis. Results of water level obtained by applying the analytical model to a tidal reach of the Keum River in the years 1981 and 1982 show very good agreement with those obtained from the harmonic analysis.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2821-2823
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• 2002

In this paper we propose the Multi-FNN (Fuzzy-Neural Networks) for optimal identification modeling of complex system. The proposed Multi-FNNs is based on a concept of FNNs and exploit linear inference being treated as generic inference mechanisms. In the networks learning, backpropagation(BP) algorithm of neural networks is used to updata the parameters of the network in order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM(Hard C-Means)clustering algorithm which carry out the input-output dat a preprocessing function and Genetic Algorithm which carry out optimization of model The HCM clustering method is utilized to determine the structure of Multi-FNNs. The parameters of Multi-FNN model such as apexes of membership function, learning rates, and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization abilities of the model. NOx emission process data of gas turbine power plant is simulated in order to confirm the efficiency and feasibility of the proposed approach in this paper.

• Journal of Ocean Engineering and Technology
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• v.7 no.1
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• pp.13-24
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• 1993

The dispersion in the oscillatory flow generated by gravitational waves above the spatially periodic repples is studied. The steady parts of equations describing the orbit of the passive particle in a two dimensional field are assumed to be simply trigonometric functions. From the view point of nonlinear dynamics, the motion of the particle is chaotic under externally time-periodic perturbations which come from the wave motion. Two cases considered here are; (i) shallow water, and (ii) deep water approximation.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.47.2-47.2
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• 2016

The protons and helium ions in the solar wind are observed to possess anisotropic temperature profiles. The anisotropy appears to be limited by various marginal instability conditions. One of the efficient methods to investigate the global dynamics and distribution of various temperature anisotropies in the large-scale solar wind models may be that based upon the macroscopic quasi-linear approach. The present paper investigates the proton and helium ion anisotropy instabilities on the basis of comparison between the quasi-linear theory versus particle-in-cell simulation. It is found that the overall dynamical development of the particle temperatures is quite accurately reproduced by the macroscopic quasi-linear scheme. The wave energy development in time, however, shows somewhat less restrictive comparisons, indicating that while the quasi-linear method is acceptable for the particle dynamics, the wave analysis probably requires higher-order physics, such as wave-wave coupling or nonlinear wave-particle interaction. We carried out comparative studies of proton firehose instability, aperiodic ordinary mode instability, and helium ion anisotropy instability. It was found that the agreement between QL theory and PIC simulation is rather good. It means that the quasilinear approximation enjoys only a limited range of validity, especially for the wave dynamics and for the relatively high-beta regime.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.69.1-69.1
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• 2014

We perform an MHD simulation combined with observed vector field data to clarify an eruptive dynamics in the solar flare. We first extrapolate a 3D coronal magnetic field under a Nonlinear Force-Free Field (NLFFF) approximation based on the vector field, and then we perform an MHD simulation where the NLFFF prior to the flare is set as an initial condition. Vector field was obtained by the Soar Dynamics Observatory (SDO) at 00:00 UT on February 15, which is about 90 minutes before the X2.2-class flare. As a result, the MHD simulation successfully shows an eruption of strongly twisted lines whose values are over one-turn twist, which are produced through the tether-cut magnetic reconnection in strongly twisted lines of the NLFFF. Eventually, we found that they exceed a critical height at which the flux tube becomes unstable to the torus instability determining the condition that whether a flux tube might escape from the overlying field lines or not. In addition to these, we found that the distribution of the observed two-ribbon flares is similar to the spatial variance of the footpoints caused by the reconnection of the twisted lines being resided above the polarity inversion line. Furthermore, because the post flare loops obtained from MHD simulation well capture that in EUV image taken by SDO, these results support the reliability of our simulation.

• Journal of the Society of Naval Architects of Korea
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• v.34 no.1
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• pp.93-101
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• 1997

Generally the traditional optimization methods have possibilities not only to give a different optimum value according to their starting point, but also to get to local optima. On the other hand, Genetic Algorithm (GA) has an ability of robust global search. In this paper, a new optimization method - the combination of traditional optimization method and genetic algorithm - is presented so as to overcome the above disadvantage of traditional methods. In order to increase the efficiency of the hybrid optimization method, a knowledge-based reasoning is adopted in the part of mathematical modeling, algorithm selection, and process control. The validation of the developed knowledge-based hybrid optimization method was examined and verified applying the method to nonlinear mathematical models.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2627-2629
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• 2003

In this paper, we propose a new architecture of Genetic Algorithms(GAs)-based Self-Organizing Polynomial Neural Networks(SOPNN). The conventional SOPNN is based on the extended Group Method of Data Handling(GMDH) method and utilized the polynomial order (viz. linear, quadratic, and modified quadratic) as well as the number of node inputs fixed (selected in advance by designer) at Polynomial Neurons (or nodes) located in each layer through a growth process of the network. Moreover it does not guarantee that the SOPNN generated through learning has the optimal network architecture. But the proposed GA-based SOPNN enable the architecture to be a structurally more optimized networks, and to be much more flexible and preferable neural network than the conventional SOPNN. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the GA-based SOPNN, the model is experimented with using nonlinear system data.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.3
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• pp.39-46
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• 2005

In this paper, adaptive higher harmonic control technique using Neural Networks (NN) is proposed. First, linear transfer function is estimated to relate the input harmonics and output harmonics, then NN which has the universal function approximation property is applied to expand application range of the transfer function. Optimal control gain matrix computed from the transfer function is used to train NN weights. Online weight adaptation laws are derived from Lyapunov's direct method to guarantee internal stability. Results of the simulation of 6-input 2-output nonlinear system show that adaptive HHC is applicable to the system with uncertain transfer function.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.685-686
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• 2007

This paper presents an application of power system fault diagnostic algorithm for the PEFP Proton Accelerator Research Center using neural network. Proposed fault diagnostic system is constructed by the radial basis function (RBF) neural network because it has the capabilities of the pattern classification and function approximation of any nonlinear function. Proposed system identifies faulted section in the power system based on information about the operation of protection devices such as relays and circuit breakers. In this paper, parameters of the RBF neural networks are tuned by the GA-TS algorithm, which has the global optimal solution searching capabilities. To show the validity of the proposed method, proposed algorithm has been tested with a practical power system in Proton Accelerator Research Center of PEFP.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.23 no.3
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• pp.111-116
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• 1987

The accurate prediction of the ship wave resistance is very important to design ships which operate satisfactorily in a wave environment. Thus, work should continue on development and validation of methods to compute ship wave patterns and wave resistance. Research efforts to improve the prediction of ship waves and wavemaking resistance are categorized in two major areas. First is the development of higher-order theories to take account of the nonlinear effect of the free surface condition and improved analytical treatment of the body boundary condition. Second is the development of direct numerical methods aimed at solving body and free-surface boundary conditions as accurately as possible. A new formulation of the slender body theory for a ship with constant speed is developed by Maruo. It is quite different from the existing slender ship theory by Vossers, Maruo and Tuck. It may be regarded as a substitute for the Neumann-Kelvin approximation. In present work, the method of asymptotic expansion of the Kelvin source is applied to obtain a new wave resistance formulation in fluid of finite depth. It takes a simple form than existing theory.