• Proceedings of the Korea Water Resources Association Conference
• /
• 2010.05a
• /
• pp.1596-1599
• /
• 2010

Group method of data handling neural networks model (GMDH-NNM) is used to estimate daily pan evaporation (PE) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$), mean relative humidity ($RH_{mean}$) and sunshine duration (SD). And, for the performances of GMDH-NNM, it is composed of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of GMDH-NNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily PE data using GMDH-NNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as pan evaporation modeling can be generalized using GMDH-NNM.

• The Transactions of the Korean Institute of Electrical Engineers B
• /
• v.54 no.9
• /
• pp.422-430
• /
• 2005

This paper describes experimental analysis of UPFC, which is composed of cascaded H-bridge modules and single-phase multi-winding transformers for isolation. The operational characteristic was analyzed through experimental works with a scaled model, and simulation results with PSCAD/EMTDC. The UPFC proposed in this paper can be directly connected to the transmission line without series injection transformers. It has flexibility to expand the operation voltage by increasing the number of H-bridge modules. The analysis results can be utilized to design the actual WFC system applicable for the transmission system.

• Journal of Electrical Engineering and Technology
• /
• v.7 no.6
• /
• pp.807-813
• /
• 2012

In this paper, we introduce data mining techniques for short-term load forecasting (STLF). First, we use the K-mean algorithm to classify historical load data by season into four patterns. Second, we use the k-NN algorithm to divide the classified data into four patterns for Mondays, other weekdays, Saturdays, and Sundays. The classified data are used to develop a time series forecasting model. We then forecast the hourly load on weekdays and weekends, excluding special holidays. The historical load data are used as inputs for load forecasting. We compare our results with the KEPCO hourly record for 2008 and conclude that our approach is effective.

• Proceedings of the KIEE Conference
• /
• 2003.07b
• /
• pp.738-740
• /
• 2003

A lot of R&D on the diagnosis of stator winding insulation for large rotating machines has been carried out since the 1970s. The on-line partial discharge measurement has proved to be an effective technique in the evaluation of the state of stator insulation in high voltage rotating machines. It is well known that if the discharge pulses propagate through the winding conductor, they are attenuated and delayed. In the present study, to investigate the attenuation and the time delay of discharge pulses through the winding conductor, a series of tests were conducted using a model coils and slot. Thus it could be concluded that while the high frequency pulse propagates in radiation or end-winding coupling modes, the low frequency one does in a series mode through the coil conductor.

• Proceedings of the KIEE Conference
• /
• 1993.07b
• /
• pp.850-852
• /
• 1993

A buck-boost zero current switched(ZCS) series resonant AC to DC converter for the DC output voltage regulation together with high power factor is proposed. A dynamic model for this AC to DC converter is developed and an analysis for the internal operational characteristics is explored. With the proposed control technique, the unity power factor and the DC output voltage regulation without a current overshoot can be obtained.

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.917-919
• /
• 2003

This paper demonstrates that RADARSAT ScanSAR data can be an important data source of radar remote sensing for monitoring crop systems and estimation of rice yield for large areas in tropic and sub-tropical regions. Experiments were carried out to show the effectiveness of RADARSAT ScanSAR data for rice yield estimation in whole province of Guangdong, South China. A methodology was developed to deal with a series of issues in extracting rice information from the ScanSAR data, such as topographic influences, levels of agro-management, irregular distribution of paddy fields and different rice cropping systems. A model was provided for rice yield estimation based on the relationship between the backscatter coefficient of multi-temporal SAR data and the biomass of rice.

• Proceedings of the KIEE Conference
• /
• 1995.07a
• /
• pp.271-273
• /
• 1995

Hybrid active filters utilize passive filters to reduce the voltage rating and hence the VA rating of the active filter converter. A novel hybrid active filter topoloty to minimize utility current harmonics at high power levels is presented in this paper. The proposed topology combines both passive and active filters to obtain the lowest converter VA rating as compared to the converter rating in the active filter and the series-active hybrid filter configurations. This is demonstrated with experimental results from a laboratory model. Simulation results showing the effect of passive filter impedance are presented.

• Communications for Statistical Applications and Methods
• /
• v.17 no.2
• /
• pp.255-261
• /
• 2010

A class of threshold-asymmetric GRACH(TGARCH, hereafter) models has been useful for explaining asymmetric volatilities in the field of financial time series. The cumulative impulse response function of a conditionally heteroscedastic time series often measures a degree of unstability in volatilities. In this article, a general form of the cumulative impulse response function of the TGARCH model is discussed. In particular, We present formula in their closed forms for the first two lower order models, viz., TGARCH(1, 1) and TGARCH(2, 2).

• Journal of Korean Society of Water and Wastewater
• /
• v.12 no.4
• /
• pp.43-52
• /
• 1998

The purpose of this study is to establish a method of estimating the daily urban water demend using Backpropagation algorithm is part of ANN(Artificial Neural Network). This method will be used for the development of the efficient management and operations of the water supply facilities. The data used were the daily urban water demend, the population and weather conditions such as treperarture, precipitation, relative humidity, etc. Kwangju city was selected for the case study area. We adjusted the weights of ANN that are iterated the training data patterns. We normalized the non-stationary time series data [-1,+1] to fast converge, and choose the input patterns by statistical methods. We separated the training and checking patterns form input date patterns. The performance of ANN is compared with multiple-regression method. We discussed the representation ability the model building process and the applicability of ANN approach for the daily water demand. ANN provided the reasonable results for time series forecasting.

• Journal of Power Electronics
• /
• v.17 no.6
• /
• pp.1545-1552
• /
• 2017

Identifying the load and mutual inductance is essential for improving the power transfer capability and power transfer efficiency of Inductive Power Transfer (IPT) systems. In this paper, a steady-state load and mutual inductance identification method focusing on series-parallel compensated IPT systems is proposed. The identification model is established according to the steady-state characteristics of the system. Furthermore, two sets of identification results are obtained, and then they are analyzed in detail to eliminate the untrue one. In addition, the identification method can be achieved without extra circuits so that it does not increase the complexity of the system or the control difficulty. Finally, the feasibility of the proposed method has been verified by simulation and experimental results.