• Korean Journal of Construction Engineering and Management
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• v.12 no.2
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• pp.111-120
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• 2011

High-rise buildings have recently increased over the residential, commercial and office facilities, thus an understanding of construction cost for high-rise building projects has been a fundamental issue due to enormous construction cost as well as unpredictable market conditions and fluctuations in the rate of inflation by long-term construction periods of high-rise projects. Especially, recent violent fluctuations of construction material prices add to problems in construction cost forecasting. This research, therefore, develops a time-series model with the Box-Jenkins methodologies and material prices time-series data in Korea in order to forecast future trends of unit prices of required materials. BIM (Building Information Modeling) approaches are also used to analyze injection time of construction resources and to conduct quantity takeoff so that total material price can be forecasted. Comparative analysis of Predictability of tentative ARIMA (Autoregressive Integrated Moving Average) models was conducted to determine optimal time-series model for forecasting future price trends. Proposed BIM based time series forecasting model can help to deal with sudden changes in economic conditions by estimating future material prices.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.243-255
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• 1997

Forecasting the future values of an observed time series is an important problem in many areas, including economics, traffic engineering, production planning, sales forecasting, and stock control. The purpose of this paper is aimed to discover the more efficient forecasting model through the parameter estimation and residual analysis among the quantitative method such as Winters' exponential smoothing model, Box-Jenkins' model, and Kalman filtering model. The mean of the time series is assumed to be a linear combination of known functions. For a parameter estimation and residual analysis, Winters', Box-Jenkins' model use Statgrap and Timeslab software, and Kalman filtering utilizes Fortran language. Therefore, this paper can be used in real fields to obtain the most effective forecasting model.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.3
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• pp.364-372
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• 2007

The ozone concentration is one of the important environmental issue for measurement of the atmospheric condition of the country. In this article, two time series ARE models, the direct ARE model and applied ARE model have been considered for analyzing the ozone data at southern part of the Gyeonggi-Do, Pyeongtaek, Osan and Suwon monitoring sites in Korea. The result shows that the direct ARE model is better suited for describing the ozone concentration in all three sites. In both of the ARE models, eight meteorological variables and four pollution variables are used as the explanatory variables. Also the high level of ozone data (over 80 ppb) have been analyzed at the Pyeongtaek, Osan and Suwon monitoring sites.

• Communications for Statistical Applications and Methods
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• v.22 no.1
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• pp.31-40
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• 2015

This study proposes a mathematical model that can forecast national defense expenditures. The ongoing European debt crisis weighs heavily on markets; consequently, government spending in many countries will be constrained. However, a forecasting model to predict military spending is acutely needed for South Korea because security threats still exist and the estimation of military spending at a reasonable level is closely related to economic growth. This study establishes two models: an Auto-Regressive Moving Average model (ARIMA) based on past military expenditures and Transfer Function model with the Gross Domestic Product (GDP), exchange rate and consumer price index as input time series. The proposed models use defense spending data as of 2012 to create defense expenditure forecasts up to 2025.

• Journal of Information Technology Applications and Management
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• v.27 no.2
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• pp.37-50
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• 2020

This paper is very exploratory and addresses the issue 'Is a general quality model of software possible?'. If possible, how specific can/should it be?' ISO 25000 Series SQuaRE is generally regarded as a general quality model which can be applied to most kinds of software. Usability is one of the 8 characteristics of SQuaRE's Product Quality Model. It is the main issue associated with SQuaRE's Quality in Use Model too. it is the most important concept associated software quality since using is the only ultimate goal of software products. Playability, however, is generally regarded as a special type of usability, which can be applied to game software. This common idea contradicts with the idea that SQuaRE is valid for most kinds, at least many kinds, of software. The empirical evidences of this paper show that SQuaRE is too specific to be a general quality model of software.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1551-1559
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• 2013

In this paper, we analyze the Korean Won/Japanese 100 Yen exchange rate data based on the ARMA-GARCH model, and perform the test for detecting the parameter changes. As a test statistics, we employ the cumulative sum (CUSUM) test for ARMA-GARCH model, which is introduced by Lee and Song (2008). Our empirical analysis indicates that the KRW/JPY exchange rate series experienced several parameter changes during the period from January 2000 to December 2012, which leads to a fitting of AR-IGARCH model to the whole series.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.4
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• pp.607-612
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• 1994

The static and dynamic model of IGBT for the SPICE simulation has been successfully developed. The various circuit model parameters are extracted from the I-V and C-V characteristics of IGBT and implemented into our model. The static model of IGBT consists of the MOSFET, bipolar transistor and series resistance. The parameters to be extracted are the threshold voltage of MOSFET, current gain $\beta$ of bipolar transistor, and the series resistance. They can be extracted from the measured I-V characteristics curve. The C-V characteristics between the terminals are very important parameters to determine the turn-on and turn-off waveform. Especially, voltage dependent capacitance are polynomially approximated to obtain the exact turn-on and turn-off waveforms. The SPICE simulation results employing new model agree well with the experimental values.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.4
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• pp.511-516
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• 1996

In this paper, weekly maximum power demand forecasting method in consideration of temperature estimation using a time series model was presented. The method removing weekly, seasonal variations on the load and irregularities variation due to unknown factor was presented. The forecasting model that represent the relations between load and temperature which get a numeral expected temperature based on the past 30 years(1961~1990) temperature was constructed. Effect of holiday was removed by using a weekday change ratio, and irregularities variation was removed by using an autoregressive model. The results of load forecasting show the ability of the method in forecasting with good accuracy without suffering from the effect of seasons and holidays. Percentage error load forecasting of all seasons except summer was obtained below 2 percentage. (author). refs., figs., tabs.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.6
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• pp.477-483
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• 2020

This study proposes a DQ synchronous reference frame model of a series-parallel tuned inductive power transfer (SP-IPT) system. The wireless power transmission system experiences control difficulty because the transmitter-side controller cannot directly measure the receiver-side load voltages and currents. Therefore, a control-oriented circuit model that shows the dynamics of the IPT system is required to achieve a well-behaved controller. In this study, an equivalent circuit model of the SP-IPT system in a synchronously rotating reference frame is proposed using the single-phase DQ transformation technique. The proposed circuit model is helpful in modeling the dynamics of the voltages and currents of the transmitter- and receiver-side resonant tanks and loads. The proposed circuit model is evaluated using frequency- and time-domain simulation results.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.225-233
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• 2011

Stock market prices, economic indices, trends and changes of social phenomena, etc. are categorized as time series data. Research on time series data has been prevalent for a while as it could not only lead to valuable representation of data but also provide future trends as well as changes in direction. We take a conventional model based approach, known as Markov chain modeling for the prediction on stock market prices. To improve prediction accuracy, we apply Markov modeling over carefully selected intervals of training data to fit the trend under consideration to the model. Another method we take is to apply clustering to data and build models of the resultant clusters. We confirmed that clustered models are better off in predicting, however, with the loss of prediction rate.