• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.1060-1069
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• 2016

In this paper, we introduce the fingerprint recognition system based on Radial Basis Function Neural Network(RBFNN). Fingerprints are classified as four types(Whole, Arch, Right roof, Left roof). The preprocessing methods such as fast fourier transform, normalization, calculation of ridge's direction, filtering with gabor filter, binarization and rotation algorithm, are used in order to extract the features on fingerprint images and then those features are considered as the inputs of the network. RBFNN uses Fuzzy C-Means(FCM) clustering in the hidden layer and polynomial functions such as linear, quadratic, and modified quadratic are defined as connection weights of the network. Particle Swarm Optimization (PSO) algorithm optimizes a number of essential parameters needed to improve the accuracy of RBFNN. Those optimized parameters include the number of clusters and the fuzzification coefficient used in the FCM algorithm, and the orders of polynomial of networks. The performance evaluation of the proposed fingerprint recognition system is illustrated with the use of fingerprint data sets that are collected through Anguli program.

• International Journal of Naval Architecture and Ocean Engineering
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• v.9 no.5
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• pp.499-508
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• 2017

This paper uses optimization techniques to obtain bow hull form of a 66,000 DWT bulk carrier in calm water and in waves. Parametric modification functions of SAC and section shape of DLWL are used for hull form variation. Multi-objective functions are applied to minimize the wave-making resistance in calm water and added resistance in regular head wave of ${\lambda}/L=0.5$. WAVIS version 1.3 is used to obtain wave-making resistance. The modified Fujii and Takahashi's formula is applied to obtain the added resistance in short wave. The PSO algorithm is employed for the optimization technique. The resistance and motion characteristics in calm water and regular and irregular head waves of the three hull forms are compared. It has been shown that the optimal brings 13.2% reduction in the wave-making resistance and 13.8% reduction in the added resistance at ${\lambda}/L=0.5$; and the mean added resistance reduces by 9.5% at sea state 5.

• Journal of Electrical Engineering and Technology
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• v.7 no.6
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• pp.814-823
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• 2012

Electric power transmission utilities make an effort to maximize profit by reducing their electricity supply and operation costs while maintaining their reliability. The development of maintenance strategies for aged components is one of the more effective ways to achieve this goal. The reliability centered approach is a key method in providing optimal maintenance strategies. It considers the tradeoffs between the upfront maintenance costs and the potential costs incurred by reliability losses. This paper discusses the application of the Particle Swarm Optimization (PSO) technique used to find the optimal maintenance strategy for a transmission component in order to achieve the minimum total expected cost composed of Generation Cost (GC), Maintenance Cost (MC), Repair Cost (RC) and Outage Cost (OC). Three components of a transmission system are considered: overhead lines, underground cables and insulators are considered. In regards to aged and aging component, a component state model that uses a modified Markov chain is proposed. A simulation has been performed on an IEEE 9-bus system. The results from this simulation are quite encouraging, and then the proposed approach will be useful in practical maintenance scheduling.

• Structural Engineering and Mechanics
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• v.76 no.4
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• pp.451-463
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• 2020

In this paper, a new semi-analytical solution for estimating the pull-in parameters of electrically actuated functionally graded (FG) nanobeams is proposed. All the bulk and surface material properties of the FG nanoactuator vary continuously in thickness direction according to power law distribution. Here, the modified couple stress theory (MCST) and Gurtin-Murdoch surface elasticity theory (SET) are jointly employed to capture the size effects of the nanoscale beam in the context of Euler-Bernoulli beam theory. According to the MCST and SET and accounting for the mid-plane stretching, axial residual stress, electrostatic actuation, fringing field, and dispersion (Casimir or/and van der Waals) forces, the nonlinear nonclassical equation of motion and boundary conditions are obtained derived using Hamilton principle. The proposed semi-analytical solution is derived by employing Galerkin method in conjunction with the Particle Swarm Optimization (PSO) method. The proposed solution approach is validated with the available literature. The freestanding behavior of nanoactuators is also investigated. A parametric study is conducted to illustrate the effects of different material and geometrical parameters on the pull-in response of cantilever and doubly-clamped FG nanoactuators. This model and proposed solution are helpful especially in mechanical design of micro/nanoactuators made of FGMs.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.3
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• pp.821-831
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• 2014

Stochastic rainfall generators or stochastic simulation have been widely employed to generate synthetic rainfall sequences which can be used in hydrologic models as inputs. The calibration of Poisson cluster stochastic rainfall generator (e.g. Modified Bartlett-Lewis Rectangular Pulse, MBLRP) is seriously affected by local minima that is usually estimated from the local optimization algorithm. In this regard, global optimization techniques such as particle swarm optimization and shuffled complex evolution algorithm have been proposed to better estimate the parameters. Although the global search algorithm is designed to avoid the local minima, reliable parameter estimation of MBLRP model is not always feasible especially in a limited parameter space. In addition, uncertainty associated with parameters in the MBLRP rainfall generator has not been properly addressed yet. In this sense, this study aims to develop and test a Bayesian model based parameter estimation method for the MBLRP rainfall generator that allow us to derive the posterior distribution of the model parameters. It was found that the HBM based MBLRP model showed better performance in terms of reproducing rainfall statistic and underlying distribution of hourly rainfall series.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2388-2398
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• 2017

In this study, we propose a robust face recognition system to pose variations based on automatic pose estimation. Radial basis function neural network is applied as one of the functional components of the overall face recognition system. The proposed system consists of preprocessing and recognition modules to provide a solution to pose variation and high-dimensional pattern recognition problems. In the preprocessing part, principal component analysis (PCA) and 2-dimensional 2-directional PCA ($(2D)^2$ PCA) are applied. These functional modules are useful in reducing dimensionality of the feature space. The proposed RBFNNs architecture consists of three functional modules such as condition, conclusion and inference phase realized in terms of fuzzy "if-then" rules. In the condition phase of fuzzy rules, the input space is partitioned with the use of fuzzy clustering realized by the Fuzzy C-Means (FCM) algorithm. In conclusion phase of rules, the connections (weights) are realized through four types of polynomials such as constant, linear, quadratic and modified quadratic. The coefficients of the RBFNNs model are obtained by fuzzy inference method constituting the inference phase of fuzzy rules. The essential design parameters (such as the number of nodes, and fuzzification coefficient) of the networks are optimized with the aid of Particle Swarm Optimization (PSO). Experimental results completed on standard face database -Honda/UCSD, Cambridge Head pose, and IC&CI databases demonstrate the effectiveness and efficiency of face recognition system compared with other studies.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.639-642
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• 2003

This paper presents a method for evaluating the mixed nash equilibria of the Cournot model for N-Gencos. in wholesale electricity market. In the wholesale electricity market, the strategies of N-Genco. can be applied to the game model under the conditions which the Gencos. determine their stratgies to maximize their benefit. Generally, the Lemke algorithm is evaluated the mixed nash equlibria in the two-player game model. However, the necessary condition for the mixed equlibria of N-player are modified as the necessary condition of N-1 player by analyzing the Lemke algorithms. Although reducing the necessary condition for N-player as the one of N-1 player, it is difficult to and the mixed nash equilibria participated two more players by using the mathmatical approaches since those have the nonlinear characteristics. To overcome the above problem, this paper presents the generalized necessary condition for N-player and proposed the object function to and the mixed nash equlibrium. Also, to evaluate the mixed equilibrium through the nonlinear objective function, the Particle Swarm Optimization (PSO) as one of the heuristic algorithm are proposed in this paper. To present the mixed equlibria for the strategy of N-Gencos. through the proposed necessry condition and the evaluation approach, this paper proposes the mixed equilibrium in the cournot game model for 3-players.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.259-276
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• 2024

The undrained shear strength is widely acknowledged as a fundamental mechanical property of soil and is considered a critical engineering parameter. In recent years, researchers have employed various methodologies to evaluate the shear strength of soil under undrained conditions. These methods encompass both numerical analyses and empirical techniques, such as the cone penetration test (CPT), to gain insights into the properties and behavior of soil. However, several of these methods rely on correlation assumptions, which can lead to inconsistent accuracy and precision. The study involved the development of innovative methods using extreme gradient boosting (XGB) to predict the pile set-up component "A" based on two distinct data sets. The first data set includes average modified cone point bearing capacity (q_t), average wall friction (f_s), and effective vertical stress (σ_vo), while the second data set comprises plasticity index (PI), soil undrained shear cohesion (S_u), and the over consolidation ratio (OCR). These data sets were utilized to develop XGBoost-based methods for predicting the pile set-up component "A". To optimize the internal hyperparameters of the XGBoost model, four optimization algorithms were employed: Particle Swarm Optimization (PSO), Social Spider Optimization (SSO), Arithmetic Optimization Algorithm (AOA), and Sine Cosine Optimization Algorithm (SCOA). The results from the first data set indicate that the XGBoost model optimized using the Arithmetic Optimization Algorithm (XGB - AOA) achieved the highest accuracy, with R2 values of 0.9962 for the training part and 0.9807 for the testing part. The performance of the developed models was further evaluated using the RMSE, MAE, and VAF indices. The results revealed that the XGBoost model optimized using XGBoost - AOA outperformed other models in terms of accuracy, with RMSE, MAE, and VAF values of 0.0078, 0.0015, and 99.6189 for the training part and 0.0141, 0.0112, and 98.0394 for the testing part, respectively. These findings suggest that XGBoost - AOA is the most accurate model for predicting the pile set-up component.

• Journal of Korean Society of Water and Wastewater
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• v.37 no.4
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• pp.177-186
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• 2023

Perfluorooctanoic acid(PFOA) was one of widely used per- and poly substances(PFAS) in the industrial field and its concentration in the surface and groundwater was found with relatively high concentration compared to other PFAS. Since various processes have been introduced to remove the PFOA, adsorption using GAC is well known as a useful and effective process in water and wastewater treatment. Surface modification for GAC was carried out using Cu and Fe to enhance the adsorption capacity and four different adsorbents, such as GAC-Cu, GAC-Fe, GAC-Cu(OH)₂, GAC-Fe(OH)₃ were prepared and compared with GAC. According to SEM-EDS, the increase of Cu or Fe was confirmed after surface modification and higher weight was observed for Cu and Fe hydroxide(GAC-Cu(OH)₂ and GAC-Fe(OH)₃, respectively). BET analysis showed that the surface modification reduced specific surface area and total pore volumes. The highest removal efficiency(71.4%) was obtained in GAC-Cu which is improved by 17.9% whereas the use of Fe showed lower removal efficiency compared to GAC. PFOA removal was decreased with increase of solution pH indicating electrostatic interaction governs at low pH and its effect was decreased when the point of zero charges(pzc) was negatively increased with an increase of pH. The enhanced removal of PFOA was clearly observed in solution pH 7, confirming the Cu in the surface of GAC plays a role on the PFOA adsorption. The maximum uptake was calculated as 257 and 345 ㎍/g for GAC and GAC-Cu using Langmuir isotherm. 40% and 80% of removal were accomplished within 1 h and 48 h. According to R², only the linear pseudo-second-order(pso) kinetic model showed 0.98 whereas the others obtained less than 0.870.

• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.80-85
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• 2015

In this paper, we present, an indstrial RFID layered microstrip patch antenna is designed using an inset feed method in order to improve recognition rates in a long distance as tags are attached to metal object by improving a problem of feeding power in fabricating metal tags and reducing effects of metallic object. The inset feed shows a distinctive characteristic that has no separation between emitters and feed lines differing from a structure with the conventional inductive coupling feed. This structure makes possible to produce a type that presents a low antenna height and enables impedance coupling for tag chips. Although it shows a difficulty in the impedance coupling due to increases in the parasite capacitance between a ground plane and an emitter in an antenna according to decreases in the height of a tag antenna, it may become a merit in designing the tag antenna because the antenna impedance can be determined as an inductive manner if a shorted structure is used for feeding power. Therefore, in this paper the microstrip patch antenna is designed as a modified type and applies the inset feed in order to reduce effects of metallic objects where the antenna is be attached. Also, the antenna uses a multi-layer structure that includes a metal plate between radiator and ground instead of using a single layer.