• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.11
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• pp.577-584
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• 2002

This paper presents a novel approach based on eigenvalue perturbation of augmented matrix(AMEP) to estimate the eigenvalue for variation of controller parameter. AMEP is a useful tool in the analysis and design of large scale power systems containing many different types of exciters, governors and stabilizers. Also, it can be used to find possible sources of instability and to determine the most sensitivity parameters for low frequency oscillation modes. This paper describes the application results of AMEP algorithm with respect to all controller parameter of KEPCO systems. Simulation results for interarea and local mode show that the proposed AMEP algorithm can be used for turning controller parameter, and verifying system data and linear model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.8-15
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• 2015

This paper includes a method for estimating the parameter of a synchronous generator and exciter using the modified particle swarm optimization. A solid round rotor synchronous generator and exciter have been modeled with the saturation function. They are regarded as state of being cooperative to a infinite bus. The behavior characteristic of all particles assigned to a parameter needs to be reflected in the PSO algorithm to fine out more close result to the optimal solution. The results of the simulation to estimate the parameters of the synchronous generator and exciter in the modified PSO algorithm are described.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.41-44
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• 2008

In this paper, major species of tree were discriminated in compartment by using LiDAR data and optic imagery. This is an important work in forest field. A current digital stock map has created the aerial photo and collecting survey data. Unlike high resolution imagery, LiDAR data is not influenced by topographic effects since it is an active sensory system. LiDAR system can measure three dimension information of individual tree. And the main methods of this study were to extract reliable the individual tree and analysis techniques to facilitate the used LiDAR data for calculating tree crown 2D parameter. We should estimate the forest inventory for calculating parameter. 2D parameter has need of area, perimeter, diameter, height, crown shape, etc. Eventually, major species of tree were determined the tree parameters, compared a digital stock map.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.408-412
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• 2009

In this paper, a new efficient algorithm for global motion estimation is proposed. This algorithm uses a previous 4-parameter model based global motion estimation algorithm and M-estimator for improving the accuracy and robustness of the estimate. The first algorithm uses the block based motion vector fields and which generates a coarse global motion parameters. And second algorithm is M-estimator technique for getting precise global motion parameters. This technique does not increase the computational complexity significantly, while providing good results in terms of estimation accuracy. In this work, an initial estimation for the global motion parameters is obtained using simple 4-parameter global motion estimation approach. The parameters are then refined using M-estimator technique. This combined algorithm shows significant reduction in mean compensation error and shows performance improvement over simple 4-parameter global motion estimation approach.

• Proceedings of the KIPE Conference
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• 1998.10a
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• pp.330-335
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• 1998

In this paper the robust vector control method of induction motor for the purpose of improving the system performance deterioration caused by parameter variations is proposed. The estimations of the stator current and the rotor flux are obtained by the full order state observer with corrective prediction error feedback. and the adaptive scheme is constructed to estimate the rotor speed with the error signal between real and estimation value of the stator current. Adaptive sliding observer based on the variable structure control is applied to parameter identification. Consequently predictive current control and speed sensorless vector control can be obtained simultaneously regardless of the parameter variations.

• Communications for Statistical Applications and Methods
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• v.25 no.4
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• pp.355-371
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• 2018

The two parameter negative exponential distribution has many practical applications in queuing theory such as the service times of agents in system, the time it takes before your next telephone call, the time until a radioactive practical decays, the distance between mutations on a DNA strand, and the extreme values of annual snowfall or rainfall; consequently, has many applications in reliability systems. This paper considers an estimation problem of stress-strength model with two parameter negative parameter exponential distribution. We introduce a maximum penalized likelihood method, Bayes estimator using Lindley approximation to estimate stress-strength model and compare the proposed estimators with regular maximum likelihood estimator for complete data. We also introduce a maximum penalized likelihood method, Bayes estimator using a Markov chain Mote Carlo technique for incomplete data. A Monte Carlo simulation study is performed to compare stress-strength model estimates. Real data is used as a practical application of the proposed model.

• KIEE International Transactions on Power Engineering
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• v.2A no.3
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• pp.109-113
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• 2002

This paper addresses the issue of parameter error identification and estimation in electric power systems. Parameter error identification and estimation is carried out as a part of the state estimation. A two stage estimation procedure is used to detect and identify parameter errors. Suspected parameters are identified by the WLAV state estimator in the first stage. A new WLAV state estimator adding suspected system parameters in the state vector is used to estimate the exact values of parameters. Supporting examples are given by using the IEEE 14 bus system.

• Proceedings of the KIEE Conference
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• 2001.07e
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• pp.113-115
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• 2001

This paper presents the rotor parameter identification based on the MRAS theory and the speed estimation using ANN for the sensorless vector control of induction motor. The motor speed is estimated using ANN model which contains the rotor parameter. And the rotor parameter is identified using MRAS scheme which contains the rotor speed. The rotor speed estimate converges to its actual value as the rotor parameter error converges toward the zero. The simulation using Matlab/Simulink is performed to show the effectiveness of the proposed scheme.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.297-301
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• 2005

In this paper, we propose a method to estimate camera motion parameter based on invariant point features. Typically, feature information of image has drawbacks, it is variable to camera viewpoint, and therefore information quantity increases after time. The LM(Levenberg-Marquardt) method using nonlinear minimum square evaluation for camera extrinsic parameter estimation also has a weak point, which has different iteration number for approaching the minimal point according to the initial values and convergence time increases if the process run into a local minimum. In order to complement these shortfalls, we, first propose constructing feature models using invariant vector of geometry. Secondly, we propose a two-stage calculation method to improve accuracy and convergence by using homography and LM method. In the experiment, we compare and analyze the proposed method with existing method to demonstrate the superiority of the proposed algorithms.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1123-1125
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• 2000

This paper presents the speed estimation using ANN and the rotor parameter Identification based on the MRAS theory for the sensorless induction motor drives. The motor speed is estimated using ANN model which contains the rotor parameter. And the rotor parameter is identified using MRAS scheme which contains the rotor speed. The rotor speed estimate converges to its actual value as the rotor parameter error converges toward the zero. The simulation using Matlab/Simulink is performed to verify the effectiveness of the proposed scheme.