• Journal of IKEEE
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• v.22 no.2
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• pp.455-459
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• 2018

In this paper, proposed a multi-channel charging control strategy for electric vehicle. This control strategy can adjust the charging power according to the calculated state-of-charge (SOC). Electric vehicle (EV) charging system using Particle Swarm Optimization (PSO) algorithm is proposed. A stochastic optimization algorithm technique such as PSO in the time-of-use (TOU) price used for the energy cost minimization. Simulation results show that the energy cost can be reduced using proposed method.

• Journal of Power Electronics
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• v.16 no.2
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• pp.610-620
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• 2016

The compound active clamp zero voltage soft switching (CACZVS) three-phase power factor correction (PFC) converter has many advantages, such as high efficiency, high power factor, bi-directional energy flow, and soft switching of all the switches. Triple closed-loop PI controllers are used for the three-phase power factor correction converter. The control objectives of the converter include a fast transient response, high accuracy, and unity power factor. There are six parameters of the controllers that need to be tuned in order to obtain multi-objective optimization. However, six of the parameters are mutually dependent for the objectives. This is beyond the scope of the traditional experience based PI parameters tuning method. In this paper, an improved chaotic particle swarm optimization (CPSO) method has been proposed to optimize the controller parameters. In the proposed method, multi-dimensional chaotic sequences generated by spatiotemporal chaos map are used as initial particles to get a better initial distribution and to avoid local minimums. Pareto optimal solutions are also used to avoid the weight selection difficulty of the multi-objectives. Simulation and experiment results show the effectiveness and superiority of the proposed method.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.659-668
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• 2018

This paper proposes an optimization approach of a grid-connected photovoltaic and wind hybrid energy system including energy storage considering voltage fluctuation in the electricity grid. A techno-economic analysis is carried out in order to minimize the size of hybrid system by considering the benefit-cost. Lithium-ion battery type is used for both managing the electricity selling to the grid and reducing voltage fluctuation. A new technique is developed to limit the voltage perturbation caused by the solar irradiance and the wind speed through determining the state-of-charge of battery for every hour of a day. Improved particle swarm optimization (PSO) methods, referred to as FC-VACPSO which combines Fast Convergence Particle Swarm Optimization (FCPSO) method and Variable Acceleration Coefficient Based Particle Swarm Optimization (VACPSO) method are used to solve the optimization problem. A comparative study has been performed between standard PSO method and PSO based methods to extract the best size with the benefit cost. A sensitivity analysis has been studied for different kinds and costs of batteries, by considering variable and constant state-ofcharge of battery. The simulations, performed under Matlab environment, yield good results using the FC-VACPSO method regarding the convergence and the benefit cost of the hybrid system.

• International Journal of High-Rise Buildings
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• v.1 no.2
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• pp.87-97
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• 2012

The indoor environments in high-rise buildings are generally well enclosed by defined boundary conditions. Here, a numerical simulation method based on the Lattice Boltzmann method (LBM), which aims to model and simulate the turbulent flow accurately in an enclosed environment, and its comparison with traditional computational fluid dynamics (CFD) results, are presented in this paper. CFD has become a powerful tool for predicting and evaluating enclosed airflows with the rapid advance in computer capacity and speed, and various types of CFD turbulence modeling and its application and validation have been reported. The LBM is a relatively new method; it involves solving of the discrete Boltzmann equation to simulate the fluid flow with a collision model instead of solving Navier-Stokes equations. In this study, the LBM-based scheme of flow pattern and particle dispersion analyses are validated using the benchmark test case of two- and three-dimensional and isothermal conditions (IEA/Annex 20 case); the prediction accuracy and advantages are also discussed by comparison with the results of CFD.

• Journal of the Society of Naval Architects of Korea
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• v.44 no.4
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• pp.398-407
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• 2007

A smoothed particle hydrodynamics (SPH) method is applied for simulating two-dimensional free-surface problems. The SPH method based on the Lagrangian formulation provides realistic flow motions with violent surface deformation, fragmentation and reunification. In this study, the effect of computational parameters in SPH simulation is explored through two-dimensional dam-breaking and sloshing problem. The parameters to be considered are the speed of sound, the frequency of density re-initialization, the number of particle and smoothing length. Through a series of numerical test. detailed information was obtained about how SPH solution can be more stabilized and improved by adjusting computational parameters. Finally, some numerical simulations for various fluid flow problem were carried out based on the parameters chosen through the sensitivity study.

• Knowledge Management Research
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• v.10 no.4
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• pp.17-30
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• 2009

This study is concerned with suggesting a new clustering algorithm to evaluate the value of papers which were supported by research grants by Korea Research Fund (KRF). The algorithm is based on an extended version of a conventional PSO (Particle Swarm Optimization) mechanism. In other words, the proposed algorithm is based on integration of k-means algorithm and simulated annealing mechanism, named KASA-PSO. To evaluate the robustness of KASA-PSO, its clustering results are evaluated by research grants experts working at KRF. Empirical results revealed that the proposed KASA-PSO clustering method shows improved results than conventional clustering method.

• Journal of KIISE:Software and Applications
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• v.37 no.1
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• pp.80-84
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• 2010

Tracking hands is an essential technique for hand gesture recognition which is an efficient way in Human Computer Interaction (HCI). Recently, many researchers have focused on hands tracking using a 3D hand model and showed robust tracking results compared to using 2D hand models. In this paper, we propose a novel 3D hand tracking method based on a coupled particle filter. This provides robust and fast tracking results by estimating each part of global hand poses and local finger motions separately and then utilizing the estimated results as a prior for each other. Furthermore, in order to improve the robustness, we apply a multi-cue based method by integrating a color-based area matching method and an edge-based distance matching method. In our experiments, the proposed method showed robust tracking results for complex hand motions in a cluttered background.

• Computers and Concrete
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• v.8 no.6
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• pp.677-692
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• 2011

Particle packing on meso-level has a significant influence on workability of fresh concrete and also on the mechanical and durability properties of the matured material. It was demonstrated earlier that shape exerts but a marginal influence on the elastic properties of concrete provided being packed to the same density, which is not necessarily the case with different types of aggregate. Hence, elastic properties of concrete can be treated as approximately structure-insensitive parameters. However, fracture behaviour can be expected structure-sensitive. This is supported by the present study based on discrete element method (DEM) simulated three-phase concrete, namely aggregate, matrix and interfacial transition zones (ITZs). Fracture properties are assessed with the aid of a finite element method (FEM) based on the damage materials model. Effects on tensile strength due to grain shape and packing density are investigated. Shape differences are shown to have only modest influence. Significant effects are exerted by packing density and physical-mechanical properties of the phases, whereby the ITZ takes up a major position.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7775-7780
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• 2014

This paper addresses cancer prediction based on radial basis function neural network optimized by particle swarm optimization. Today, cancer hazard to people is increasing, and it is often difficult to cure cancer. The occurrence of cancer can be predicted by the method of the computer so that people can take timely and effective measures to prevent the occurrence of cancer. In this paper, the occurrence of cancer is predicted by the means of Radial Basis Function Neural Network Optimized by Particle Swarm Optimization. The neural network parameters to be optimized include the weight vector between network hidden layer and output layer, and the threshold of output layer neurons. The experimental data were obtained from the Wisconsin breast cancer database. A total of 12 experiments were done by setting 12 different sets of experimental result reliability. The findings show that the method can improve the accuracy, reliability and stability of cancer prediction greatly and effectively.

• Nuclear Engineering and Technology
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• v.53 no.10
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• pp.3264-3274
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• 2021

In a severe accident of light water reactor (LWR), molten core material (corium) can be released into the wet cavity, and a fuel-coolant interaction (FCI) can occur. The molten jet with high speed is broken and fragmented into small debris, which may cause a steam explosion or a molten core concrete interaction (MCCI). Since the premixing stage where the jet breakup occurs has a large impact on the severe accident progression, the understanding and evaluation of the jet breakup phenomenon are highly important. Therefore, in this study, the jet breakup simulations were performed using the Smoothed Particle Hydrodynamics (SPH) method which is a particle-based Lagrangian numerical method. For the multi-fluid system, the normalized density approach and improved surface tension model (CSF) were applied to the in-house SPH code (single GPU-based SOPHIA code) to improve the calculation accuracy at the interface of fluids. The jet breakup simulations were conducted in two cases: (1) jet breakup without structures, and (2) jet breakup with structures (control rod guide tubes). The penetration depth of the jet and jet breakup length were compared with those of the reference experiments, and these SPH simulation results are qualitatively and quantitatively consistent with the experiments.