• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5422-5441
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• 2016

Despite the abundant literature in the field, there is still the need to find a time-efficient, highly accurate, easy to deploy and robust localization algorithm for real use. The algorithm only involves minimal human intervention. We propose an enhanced Received Signal Strength Indicator (RSSI) based positioning algorithm for Wi-Fi capable devices, called the Dynamic Weighted Evolution for Location Tracking (DWELT). Due to the multiple phenomena affecting the propagation of radio signals, RSSI measurements show fluctuations that hinder the utilization of straightforward positioning mechanisms from widely known propagation loss models. Instead, DWELT uses data processing of raw RSSI values and applies a weighted posterior-probabilistic evolution for quick convergence of localization and tracking. In this paper, we present the first implementation of DWELT, intended for 1D location (applicable to tunnels or corridors), and the first step towards a more generic implementation. Simulations and experiments show an accuracy of 1m in more than 81% of the cases, and less than 2m in the 95%.

• Journal of Korea Water Resources Association
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• v.37 no.2
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• pp.121-131
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• 2004

SIMHYD and TANK model are used to predict time series of daily rainfall-runoff of Soyang Dam and Youngcheon Dam watershed. The performances of SIMHYD model with 7 parameters and TANK model with17 parameters are compared. Three optimization methods (Genetic algorithm, Pattern search multi-start and Shuffled Complex Evolution algorithm) were applied to study-areas with 3 different types of objective functions. Efficiency of TANK model is higher than that of SIMHYD. Among different types of objective function, Nash-sutcliffe coefficient is found to be the most appropriateobjective function to evaluate applicability of model.

• Journal of the Korean Geographical Society
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• v.46 no.6
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• pp.673-692
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• 2011

Advances in computer technology have enabled us to develop and use numerical landscape evolution models (NLEMs) for exploring the dynamics of geomorphic system from a variety of viewpoints which previously could have not been taken. However, as of yet there have been no trials using or developing NLEMs in Korea. The purpose of this research is to develop a 2 dimensional NLEM on a geological time scale and evaluate its usefulness. The newly developed NLEM (ND-NLEM) treats bedrock weathering as one of the major geomorphic processes and attempts to simulate the thickness of soil. As such it is possible to model the weathering-limited as well as the transport-limited environment on hillslopes. Moreover the ND-NLEM includes not only slow and continuous mass transport like soil creep, but also rapid and discrete mass transport like landslides. Bedrock incision is simulated in the ND-NLEM where fluvial transport capacity is large enough to move all channel bed loads, such that ND-NLEM can model the detachment-limited environment. Furthermore the ND-NLEM adopts the D-infinity algorithm when routing flows in the model domain, so it reduces distortion due to the use of the steepest descent slope flow direction algorithm. In the experiments to evaluate the usefulness of the ND-NLEM, characteristics of the channel network observed from the model results were similar to those of the case study area for comparison, and the hypsometry curve log during the experiment showed rational evidence of landscape evolution. Therefore, the ND-NLEM is shown to be useful for simulating landscape evolution on a geological time scale.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.2
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• pp.184-189
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• 2014

In this paper, a new design method of vibration suppression controller for multi-inertia (especially, 3-ineritia) resonance systems is proposed. The controller consists of a digital fuzzy controller for speed loop and a digital PI controller for current minor loop. The three scaling factor of the fuzzy controller and two PI controller gains are determined by Differential Evolution (DE). The DE is one of optimization techniques and a kind of evolutionary computation technique. In this paper, we have applied the DE/rand/1/bin strategy to design the optimal controller parameters. Comparing with the conventional design algorithm, the proposed method is able to shorten the time of the controller design to a large extent and to obtain accurate results. Finally, we confirmed the effectiveness of the proposal method by the computer simulations.

• Transactions of Materials Processing
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• v.13 no.3
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• pp.248-252
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• 2004

The mechanical properties of polycrystalline thin-films, critical for Micro-Electro-Mechanical Systems (MEMS) components, are known to have the size effect and the scatter in the length scale of microns by the numbers of intensive investigation by experiments and simulations. So, the consideration of the microstructure is essential to cover these length scale effects. The lattice based stochastic model for the microstructure evolution is used to simulate the actual microstructure, and the fast and reliable algorithm is described in this paper. The kinetics parameters, which are the key parameters for the microstructure evolution based on the nucleation and growth mechanism, are extracted from the given micrograph of a polycrystalline material by an inverse method. And the method is verified by the comparison of the quantitative measures, the number of grains and the grain size distribution, for the actual and simulated microstructures. Finite element mesh is then generated on this lattice based microstructure by the developed code. And the statistical finite element analysis is accomplished for selected microstructure.

• Journal of Computing Science and Engineering
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• v.11 no.4
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• pp.130-141
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• 2017

Feature selection is one of the most challenging problems of pattern recognition and data mining. In this paper, a feature selection algorithm based on an improved version of binary differential evolution is proposed. The method simultaneously optimizes two feature selection criteria, namely, set approximation accuracy of rough set theory and relational algebra based derived score, in order to select the most relevant feature subset from an entire feature set. Superiority of the proposed method over other state-of-the-art methods is confirmed by experimental results, which is conducted over seven publicly available benchmark datasets of different characteristics such as a low number of objects with a high number of features, and a high number of objects with a low number of features.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.266-268
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• 2006

In this paper, we design a Linear Quadratic Gaussian(LQG) controller for active suspensions. We can improve the inherent suspension problem, trade-off between the ride quality and the suspension travel by selecting appropriate weights in the LQ-objective function. Using an optimization-algorithm, Evolution Strategy(ES), we find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle's state variables. The frequencies and proper control gains are used for the neural network data. During a vehicle running, the trained on-line neural network is activated and provides the proper gains for non-trained frequencies.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1530-1533
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• 2005

In this paper, we design a Linear Quadratic Gaussian controller for the active suspension. We can improve the inherent suspension problem, trade-off between the ride quality and the suspension travel by selecting appropriate weights in the LQ-objective function. Because any definite rules for selecting weights do not exist, we use an optimization-algorithm, Evolution Strategy (ES) to find the proper control gains for selected frequencies, which have major effects on the vibrations of the vehicle's state variables. The frequencies and proper control gains are used for the neural network data. During a vehicle running, the trained on-line neural network is activated and provides the proper gains for non-trained frequencies. For the full-state feedback control, Kalman filter observes the full states and Fourier transform is used to detect the frequency of the road.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.11
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• pp.541-546
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• 2006

In a levitation magnet system with large air gap, numerical method is needed because analytic method cannot consider the leakage flux properly. This paper conducted an optimal design of a levitation magnet system with large air gap which was used for an OLED system, where evolution strategy was adopted for optimal design algorithm. Levitation forces near the initial design were calculated first by using finite element method to reduce the computation time. During the optimization process, levitation forces of arbitrary dimension were obtained using the interpolation of the levitation forces which were calculated previously Weight of the maget system was chosen as the object function and it was used minimized.

• Journal of Sensor Science and Technology
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• v.14 no.6
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• pp.402-408
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• 2005

This paper describes the optimal design of a multi-layered surface plasmon resonance sensors to meet various specifications and improve some physical parameters. Dip 3 dB bandwidth and depth were chosen as design parameters and the objective function was the norm of the difference between design parameters and target values. The design variables are thicknesses of each layer and to obtain the design parameters, the optical admittance method was employed. The (1+1) evolution strategy was employed as an optimization tool. By applying the proposed optimization procedure to a 3-layered sensor, the optimized design variables considerably improved the 3 dB bandwidth by 4.8 nm and the dip depth by 1.1 dB.