• Journal of Fisheries and Marine Sciences Education
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• v.28 no.1
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• pp.186-197
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• 2016

This study applied the parametric bootstrapping method to analyze whether there was a change in the production efficiency of institutions under Ministry of Oceans and Fisheries. This study used input and output oriented productivity simultaneously. In particular, the productivity was estimated through 95% confidence interval derived by 2000 times re-sampling process. The results of the study showed us a reduction in overall total factor productivity by 24% between 2009 and 2013, and 7% of decreases in productivity annually. A recent conditions of an external economic shocks brought a 28% downward shift of production function. In this study, public institutions were divided into three types, which were public, quasi-government, and other public institutions. There were approximately 13%, 1%, and 5% decreases in total factor productivity per each. In analyzing the productivity each of 14 institutions, approximately DMU4 and DMU6 had 4%, and 5% increases in productivity per each. While DMU14 showed us no changes in productivity, all of the other 10 DMUs were estimated the decreases in productivities.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.204-206
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• 2007

In this study, we introduce the optimization method of fuzzy inference systems that is based on Hierarchical Fair Competition-based Parallel Genetic Algorithms (HFCGA) and information data granulation, The granulation is realized with the aid of the Hard C-means clustering and HFCGA is a kind of multi-populations of Parallel Genetic Algorithms (PGA), and it is used for structure optimization and parameter identification of fuzzy model. It concerns the fuzzy model-related parameters such as the number of input variables to be used, a collection of specific subset of input variables, the number of membership functions, the order of polynomial, and the apexes of the membership function. In the optimization process, two general optimization mechanisms are explored. The structural optimization is realized via HFCGA and HCM method whereas in case of the parametric optimization we proceed with a standard least square method as well as HFCGA method as well. A comparative analysis demonstrates that the proposed algorithm is superior to the conventional methods. Particularly, in parameter identification, we use the UNDX operator which uses multiple parents and generate offsprings around the geographic center off mass of these parents.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.207-209
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• 2007

In this paper, we introduce a genetic optimization of fuzzy set-fuzzy model using successive tuning method to carry out the model identification of complex and nonlinear systems. To identity we use genetic alrogithrt1 (GA) sand C-Means clustering. GA is used for determination the number of input, the seleced input variables, the number of membership function, and the conclusion inference type. Information Granules (IG) with the aid of C-Means clustering algorithm help determine the initial paramters of fuzzy model such as the initial apexes of the, membership functions in the premise part and the initial values of polyminial functions in the consequence part of the fuzzy rules. The overall design arises as a hybrid structural and parametric optimization. Genetic algorithms and C-Means clustering are used to generate the structurally as well as parametrically optimized fuzzy model. To identify the structure and estimate parameters of the fuzzy model we introduce the successive tuning method with variant generation-based evolution by means of GA. Numerical example is included to evaluate the performance of the proposed model.

• Journal of Electrical Engineering and Technology
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• v.8 no.3
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• pp.621-632
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• 2013

In this paper, we introduce advanced architectures of genetically-oriented Fuzzy Neural Networks (FNNs) based on fuzzy set and fuzzy relation and discuss a comprehensive design methodology. The proposed FNNs are based on 'if-then' rule-based networks with the extended structure of the premise and the consequence parts of the fuzzy rules. We consider two types of the FNNs topologies, called here FSNN and FRNN, depending upon the usage of inputs in the premise of fuzzy rules. Three different type of polynomials function (namely, constant, linear, and quadratic) are used to construct the consequence of the rules. In order to improve the accuracy of FNNs, the structure and the parameters are optimized by making use of genetic algorithms (GAs). We enhance the search capabilities of the GAs by introducing the dynamic variants of genetic optimization. It fully exploits the processing capabilities of the FNNs by supporting their structural and parametric optimization. To evaluate the performance of the proposed FNNs, we exploit a suite of several representative numerical examples and its experimental results are compared with those reported in the previous studies.

• Coupled systems mechanics
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• v.5 no.4
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• pp.285-304
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• 2016

The effects of large rotations and p-delta on the dynamic response of a structure subjected to seismic loading and local uplift of its foundation were analyzed in this work. The structure was modeled by an equivalent flexible mat mounted on a rigid foundation that is supported either by a Winkler soil type or a rigid soil. The equations of motion of the system were derived by taking into account the equilibrium of the coupled foundation-mat system where the structure was idealized as a single-degree-of-freedom. The obtained nonlinear coupled system of ordinary differential equations was integrated by using an adequate numerical scheme. A parametric study was performed then in order to evaluate the maximum response of the system as function of the intensity of the earthquake, the slenderness of the structure, the ratio of the mass of the foundation to the mass of the structure. Three cases were considered: (i) local uplift of foundation under large rotation with the p-delta effect, (ii) local uplift of foundation under large rotation without including the p-delta effect, (iii) local uplift of foundation under small rotation. It was found that, in the considered ranges of parameters and for moderate earthquakes, assuming small rotation of foundation under seismic loading can yield more adverse structural response, while the p-delta effect has almost no effect.

• 한국전산유체공학회:학술대회논문집
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• 2008.03b
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• pp.218-219
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• 2008

A gas-liquid centrifugal separator is widely used in industry because of its simple geometry and little maintenance. Also, these separators have considerable advantages over filters, scrubbers or precipitators in term of compact design, low pressure drop and higher capacity. A gas-liquid centrifugal separator is a device that utilizes centrifugal force and low pressure to separate liquid from gas by density difference. Design parameters such as length of separation space, swirl vane exit angle, inlet to outlet pipe diameter ratio, models for separation efficiency and low pressure drop as a function of physical dimension are not available in literature. In present study, length of separation space (from vane to gas exit opening) has been studied using CFD. The 3-D Navier-Stokes equations are numerically solved using a fully implicit finite volume scheme. Based upon the obtained solutions, tangential velocities, centrifugal forces, vortices and total pressure losses are analyzed to find the best design parameters.

• Advances in Computational Design
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• v.3 no.3
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• pp.289-302
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• 2018

The use of optimum content of supplementary cementing materials (SCMs) such as limestone filler (LF) to blend with Portland cement has been resulted in many environmental and technical advantages, such as increase in physical properties, enhancement of sustainability in concrete industry and reducing $CO_2$ emission are well known. Artificial neural networks (ANNs) have been already applied in civil engineering to solve a wide variety of problems such as the prediction of concrete compressive strength. The feed forward back propagation (FFBP) algorithm and Tan-sigmoid transfer function were used for the ANNs training in this study. The training, testing and validation of data during the backpropagation training process yielded good correlations exceeding 97%. A parametric study was conducted to study the sensitivity of the developed model to certain essential parameters affecting the compressive strength of concrete. The effects and benefits of limestone filler on hardened properties of the concrete such as compressive strength were well established endorsing previous results in the literature. The results of this study revealed that the proposed ANNs model showed a high performance as a feasible and highly efficient tool for simulating the LF concrete compressive strength prediction.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.634-639
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• 2003

It has been studied the flow near a rotating disk with surface topography. The system Ekman number is assumed very small, i.e., $E[{\equiv}\frac{\nu}{{\Omega}^{\ast}L^{\ast2}}]<<1$ in which $L^{\ast}$ denotes a disk radius, ${\nu}$ kinematic viscosity of the fluid and ${\Omega}^{\ast}$ angular velocity of the basic state. Disk surface has a sinusoidal topographic variation along radial coordinate, i.e., $z={\delta}cos(2{\pi}{\omega}r)$, where ${\delta}$ and ${\omega}$ are, respectively, nondimensional amplitude and wave number of the disk surface. Analytic solutions, being useful over the parametric ranges of ${\delta}{\sim}O$( $E^{1/2}$ ) and ${\omega}{\leq}O$ ( $E^{1/2}$ ), are secured in a series-function form of Fourier-Bessel type. An asymptotic behavior, when $E{\rightarrow}0$, is clarified as : for a disk with surface roughness, in contrast to the case of a flat disk, the azimuthal velocity increases in magnitude, together with the thickening boundary layer. The radial velocity, however, decreases in magnitude as the amplitude of surface waviness increases. Consequently, the overall Ekman pumping at the edge of the boundary layer remains unchanged, maintaining the constant value equal to that of the flat disk.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.127-132
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• 2003

A study of high-pressure n-heptane droplet vaporization is conducted with emphasis placed on equilibrium at vapor-liquid interface. General frame of previous rigorous model[1] is retained but tailored for flash equilibrium calculation of vapor-liquid interfacial thermodynamics. The model is based on complete time-dependent conservation equations with a full account of variable properties and vapor-liquid interfacial thermodynamics. The influences of high-pressure phenomena, including ambient gas solubility, thermodynamic non-ideality, and property variation on the droplet evaporation are investigated. The governing equations and associated moving interfacial boundary conditions are solved numerically using a implicit scheme with the preconditioning method and the dual time integration technique. And a parametric study of entire droplet vaporization history as a function of ambient pressure, temperature has been conducted. Some computational results are compared with Sato's experimental data for the validation of calculations. For low ambient temperatures, the droplet lifetime first increases with pressures, then decreases for high pressures. For higher ambient temperatures, the droplet lifetime increase with less amplitude than that of low ambient temperatures, which then decreases with more amplitude than that of low temperatures. The solubility of nitrogen can not be neglected in the high pressure and it becomes higher as the pressure goes up.

• Journal of Korea Water Resources Association
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• v.41 no.6
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• pp.559-564
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• 2008

A practical method is derived for determining the unit hydrograph and S-curve from complex storm events by using a smoothed unit kernel approach. The using a unit kernel yields more convenient way of constructing a unit hydrograph and its S-curve than a conventional method. However, with use of real data, the unit kernel oscillates and is unstable so that a unit hydrograph and S-curve cannot easily obtained. The use of non-parametric ridge regression with a Laplacian matrix is suggested for deriving an event averaged unit kernel which reduces the computational efforts when dealing with the Nash instantaneous unit hydrograph as a basis of the kernel. A method changing the unit hydrograph duration is also presented. The procedure shown in this work will play an efficient role when any unit hydrograph works is involved.