• The Journal of the Acoustical Society of Korea
• /
• v.22 no.4
• /
• pp.323-328
• /
• 2003

This study describes an energy contour generation method for Korean n systems. We propose a vector-regression tree, which is a vector version of a scalar regression tree. A vector-regression tree predicts a response vector for an unknown feature vector. In our study, the tree yields a vector containing ten sampled energy values for each phone. After collecting 500 sentences and its corresponding speech corpus, we trained trees on 300 sentences and tested them on 200 sentences. We construct a bagged tree and a born again one to improve the performance of contour prediction. In the experiment, we got a 0.803 correlation coefficient for the observed and predicted energy values.

• Journal of Korea Multimedia Society
• /
• v.21 no.7
• /
• pp.755-763
• /
• 2018

In this paper, for recognize a night pedestrian from an infrared video, a new method differentiated from the existing feature vector is proposed and experimented. The new approach focuses on the shape feature vector of the structure and shape of the pedestrian image divided by the human body seven split ratio. The pedestrian images are divided into 7 square blocks from the still image of the preprocessing process. And to reduce the dimension, the square block is converted into a mosaic block. The scalar and direction of the shape feature vector is calculated by the brightness and position of the element in the mosaic. For practicality of infrared video system, the proposed method simplifies the data to be processed by reducing the amount of data in the preprocessing in order to continuously batch process the entire system in real time. Through the experiments, we verified the validity of the proposed shape feature vector. In comparison to the existing method, we propose a new shape feature vector generation method as the feature vector for night pedestrian recognition.

• 한국전산유체공학회:학술대회논문집
• /
• 2007.04a
• /
• pp.108-111
• /
• 2007

A fast and robust method of grid generation to multiple functions has been developed for flow analysis in three dimensional space. It is based on the Non-Uniform Rational B-Spline of an approximation method. The grid generation method, details of numerical implementation. examples of application, and potential extensions of the current method are illustrated in this paper.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.21 no.7
• /
• pp.1127-1140
• /
• 1997

With the study for identifying the transmission characteristics of vibration and noise generated by operating engine system of a vehicle, recently many engineers have studied actively the reduction of vibration and noise inducing uncomfortableness to the passenger. In this study, output noise was analyzed by multi-dimensional spectral analysis and vector synthesis method. The multi-dimensional analysis method is very effective in case of identification of primary source, but this method has little effect on suggestion for interior noised reduction. For compensation of this, vector synthesis method was used to obtain effective method for interior noise reduction, after identifying primary source for output noise. In this paper, partial coherence function of each input was calculated to know which input was most coherent to output noise, then with simulation of changes for input magnitude and phase by vector synthesis diagram, the trends of synthesized output vector was obtained. As a result, the change of synthesized output vector could be estimated.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.2
• /
• pp.606-615
• /
• 1997

This paper proposes an dffcient method for test pattern generation.Current test pattern genration systems generate a test vester for fault $F_{i+l}$ independently of the computation previously done for faults F1,F2...,Fi The proposed algorithm generates a test vector for fault $F_{i+l}$ by inheriting the test vector for fault Fi. A new test vector is grnerated from inherited values by gradually changing the inhderited values .The inherited values may partially activate a fauog and propagate the fault signal,Normally,this reduses the number of decision steps and backtracks in the second search.Experimental results for well-Known benchmark circuts show that the proposed algorithm is very efficient with small backtrack kimit;in combination eith other algorithms,it is very efficient for arbitrary backtrack limits.

• Environmental and Resource Economics Review
• /
• v.28 no.4
• /
• pp.467-495
• /
• 2019

Uncertainty of renewable energy such as photovoltaic(PV) power is detrimental to the flexibility of the power system. Therefore, precise prediction of PV power generation is important to make the power system stable. The purpose of this study is to forecast PV power generation using meteorological data including particulate matter(PM). In this study, PV power generation is predicted by support vector machine using RBF kernel function based on machine learning. Comparing the forecasting performances by including or excluding PM variable in predictor variables, we find that the forecasting model considering PM is better. Forecasting models considering PM variable show error reduction of 1.43%, 3.60%, and 3.88% in forecasting power generation between 6am~8pm, between 12pm~2pm, and at 1pm, respectively. Especially, the accuracy of the forecasting model including PM variable is increased in daytime when PV power generation is high.

• Proceedings of the KIEE Conference
• /
• 2009.07a
• /
• pp.1122_1123
• /
• 2009

Doubly Fed Induction Generator (DFIG) used in variable speed constant frequency wind energy generation system can capture wind energy with the highest efficiency by using the stator flux oriented vector control method. This paper sets up a DFIG modeling of wind generation system in PSCAD/EMTDC to simulate the operational performance with wind speed variation. In order to achieve the characteristics of the maximum utilization of wind power, this paper uses the vector control technology to track largest wind power and the independent control of generator active and reactive power.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.25 no.12
• /
• pp.82-87
• /
• 2011

In this paper, a sensorless speed control system is designed for the next generation high speed railway at zero and low speed region. The applied vector control scheme is a maximum torque per ampere(MTPA) method to utilize reluctance torque of IPMSM. The designed sensorless control scheme is a rotating high frequency voltage signal injection method. To verify the designed system, a simulator for the vector controller and sensorless controller is implemented using Matlab/simulink.

• Proceedings of the KIPE Conference
• /
• 2006.06a
• /
• pp.345-347
• /
• 2006

In this paper, a novel method for wind speed estimation in wind power generation systems is presented. The proposed algorithm is based on estimating the wind speed using Support-Vector-Machines for regression (SVR). The wind speed is estimated using the generator power-speed characteristics as a set of training vectors. SVR is trained off-line to predict a continuos-valued function between the system's inputs and wind speed value. The predicted off-line function as well as the instantaneous generator power and speed are then used to determine the unknown winds speed on-line. The simulation results show that SVR can define the corresponding wind speed rapidly and accurately to determine the optimum generator speed reference for maximum power point tracking.

• Journal of Power Electronics
• /
• v.8 no.4
• /
• pp.345-353
• /
• 2008

In this paper, a novel loss minimization of an induction generator in wind energy generation systems is presented. The proposed algorithm is based on the flux level reduction, for which the generator d-axis current reference is estimated using support vector regression (SVR). Wind speed is employed as an input of the SVR and the samples of the generator d-axis current reference are used as output to train the SVR algorithm off-line. Data samples for wind speed and d-axis current are collected for the training process, which plots a relation of input and output. The predicted off-line function and the instantaneous wind speed are then used to determine the d-axis current reference. It is shown that the effect of loss minimization is more significant at low wind speed and the loss reduction is about to 40% at 4[m/s] wind speed. The validity of the proposed scheme has been verified by experimental results.