• Proceedings of the IEEK Conference
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• 2000.06e
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• pp.175-178
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• 2000

We propose a new method to deal with the optimized auto-tuning for the PID controller which is used to the process-centre] in various fields. First of all, in this method, initial values are determined by the Switched Reluctance Motor of system and Ziegler-Nichols method. After deciding binary strings of parents generation using by the fitness values of genetic algorithms, we perform selection, crossover and mutation to generate the descendant generation. The advantage of this method is better than the neural network and multiple regression model method in characteristic of output, and has extent of applying without limit of initial parameters.

• Journal of the Korean Society of Clothing and Textiles
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• v.20 no.1
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• pp.54-65
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• 1996

The purposes of this study were 1) to present the optimum slacks pattern for young men, 2) to develope a methodology to draft basic slacks pattern using AutoCAD The total crotch legth and the shape of the crutch line were determined by anthropometric data analysis. The total crotch length was calculated with the waist girth, the hip girth and the crotch length measurements. The anthropometric data utilized for this procedure was National Anthropometric Survey of Korea, 1992. And multidimensional anthropometric measurements were carried out for 6 male college students between the age of 18 to 24. The subjects were measured with the Martin's anthropometer and the sliding gauge. Mean, standard deviation and t-test were performed for statistical analysis of the data. The automatic drafting method was programmed by AutoLISP in AutoCAD. The automatic drafting was based on the Muller's slacks pattern drafting method, the measurements of slacks construction components and the curve of crotch line. The crotch line was drafted using of the arc function in AutoCAD. The total crotch length was calcuated using the multiple regression equation. The experimental pattern developed to accomodate individual body wleasurements expected to produce customized apparel production in QRS(Quick Response System) production system.

• IE interfaces
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• v.24 no.4
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• pp.351-361
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• 2011

Forecasting of electricity demand have difficulty in adapting to abrupt weather changes along with a radical shift in major regional and global climates. This has lead to increasing attention to research on the immediate and accurate forecasting model. Technically, this implies that a model requires only a few input variables all of which are easily obtainable, and its predictive performance is comparable with other competing models. To meet the ends, this paper presents an energy demand forecasting model that uses the variable selection or extraction methods of data mining to select only relevant input variables, and employs support vector regression method for accurate prediction. Also, it proposes a novel performance measure for time-series prediction, shift index, followed by description on preprocessing procedure. A comparative evaluation of the proposed method with other representative data mining models such as an auto-regression model, an artificial neural network model, an ordinary support vector regression model was carried out for obtaining the forecast of monthly electricity demand from 2000 to 2008 based on data provided by Korea Energy Economics Institute. Among the models tested, the proposed method was shown promising results than others.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2000.04a
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• pp.26-29
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• 2000

drawbead expert models are developed for calculating drawbead restraining force and drawbead-exit thinnings which are boundary conditions in FEM stamping simulation employing the linear multiple regression method by which the deviation of drawing characteristics between drawing test and mathematical model is minimized. In order to show the efficiency and accuracy of an expert drawbead model a finite element simulation of auto-body panel stamping is carried out. The finite element simulation shows that the expert drawbead model provides the accurate solution guarantees the stable convergence and the merit in the computation time.

• Journal of the Ergonomics Society of Korea
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• v.21 no.3
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• pp.59-79
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• 2002

The purposes of the study were to present the optimum slacks pattern for elementary school girls and to compare and evaluate wearing ease of the slacks. 3D scans using the Cyberware PS motion platform were carried out for 3 subjects who have different body type. The automatic drafting method was programmed by AutoLISP in CAD. Wearing tests using 3D Scanner was done for evaluation of fitness of slacks. Regression analysis, analysis of variance and post-hoc test were performed for statistical analysis of the data by SPSS program. The procedure and results were as follows: The slacks construction components for pattern drafting were derived from 10 horizontal section maps obtained from 3D scans. The automatic drafting was based on the measurements of slacks construction components and the curve of crotch line. The crotch line was drafted using of the arc function in AutoCAD. The total crotch length was calculated using the multiple regression equation. Wearing test represented that the slacks pattern developed to accomodate individual body measurements was estimated more highly than existing patterns.

• Journal of Power System Engineering
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• v.20 no.2
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• pp.66-72
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• 2016

As a method to improve the equipment reliability, early warning researches that can be detected fault symptom of an equipment at an early stage are being performed out among developed countries. In this paper, when abnormal signal is input to actual normal signal of a pump, early detection studies on pump's fault symptom were carried out with auto-associative kernel regression as an advanced pattern recognition algorithm. From analysis, correlations among power of motor driving pump, discharge flow of pump, power output of pump, and discharge pressure of pump are exited. When the abnormal signal is input to one of those normal signals, the other expected values are changed due to the influence of the abnormal signal. Therefore, the fault symptom of pump through the early-warning index is able to detect at an early stage.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.14 no.2
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• pp.1-13
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• 2015

Traffic volume data is basic information that is used in a wide variety of fields. Existing missing traffic volume data imputation method did not take the effect on the rainfall. This research analyzed considering of the rainfall effect in missing traffic volume data imputation method. In order to consider the effect of rainfall, established the following assumption. When missing of traffic volume data generated in rainy days it would be more accurate to use only the traffic volume data of the past rainy days. To confirm this assumption, compared for accuracy of imputed results at three kinds of imputation method(Unconditional Mean, Auto Regression, Expectation-Maximization Algorithm). The analysis results, the case on consideration of the rainfall effect was more low error occurred.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.4
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• pp.233-238
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• 2009

In this paper, we propose the methods to select the stable region for the detect region which is required in the system used the face to the ROI in the auto-focus digital camera. this method regards the face region as the ROI in the progressive input frame and focusing the region in the mobile camera embeded ISP module automatically. The learning algorithm to detect the face is the Adaboost algorithm. we proposed the method to detect the slanted face not participate in the train process and postprocessing method for the results of detection, and then we proposed the stabilization method to sustain the region not shake for the region. we estimated the capability for the stabilization algorithm using the RMS between the trajectory and regression curve.

• The Korean Journal of Applied Statistics
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• v.19 no.3
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• pp.421-430
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• 2006

In sample survey sample designs are performed by geographically-based domain such as countries, states and metropolitan areas. However mostly statistics of interests are smaller domain than sample designed domain. Then sample sizes are typically small or even zero within the domain of interest. Shin and Lee(2003) mentioned Spatial Autoregressive(SAR) model in small area estimation model-based method and show the effectiveness by MSE. In this study, Bayesian Auto-Poisson Model is applied in model-based small area estimation method and compare the results with SAR model using MSE ME and bias check diagnosis using regression line. In this paper Survey of Disability, Aging and Cares(SDAC) data are used for simulation studies.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.410-418
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• 1999

This paper describes the use of residual and parameter identification methods for fault detection in an air handling unit. Faults can be detected by comparing expected condition with the measured faulty data using residuals. Faults can also be detected by examining unmeasurable parameter changes in a model of a controlled system using a system identification technique. In this study, AutoRegressive Moving Average with seXtrnal input(ARMAX) and AutoRegressive with eXternal input(ARX) models with both single-input/single-input and multi-input/single-input structures are examined. Model parameters are determined using the Kalman filter recursive identification method. Regression equations are calculated from normal experimental data and are used to compute expected operating variables. These approaches are tested using experimental data from a laboratory's variable-air-volume air-handling-unit.