• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.2
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• pp.133-140
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• 2007

In this study we did the monitor the change of a urban land coverage to forecast and to deal with various city problems according to urban development. The amount of change of a land coverage used the landsat satellite image and was calculated by analyzing the situation and the distribution aspect of land cover of the road circumstance by time series. We interpreted two images which are taken picture different time and calculated the amount of the area change through integration of the spatial analysis technique of remote sensing and GIS for this study. We could create the development model of the urban area by continuous analysis of satellite and geographic data.

• Structural Monitoring and Maintenance
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• v.7 no.2
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• pp.149-166
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• 2020

This paper presents the results of an experimental investigation on a vibration-based damage identification framework for a steel girder type and a truss bridge based on acceleration responses to operational loading. The method relies on sensor clustering-based time-series analysis of the operational acceleration response of the bridge to the passage of a moving vehicle. The results are presented in terms of Damage Features from each sensor, which are obtained by comparing the actual acceleration response from the sensors to the predicted response from the time-series model. The damage in the bridge is detected by observing the change in damage features of the bridge as structural changes occur in the bridge. The relative severity of the damage can also be quantitatively assessed by observing the magnitude of the changes in the damage features. The experimental results show the potential usefulness of the proposed method for future applications on condition assessment of real-life bridge infrastructures.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2007.11a
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• pp.477-481
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• 2007

The purpose of this study is to provide the ideal forecasting model of cadastral survey work load through the Economeatric Analysis of Time Series, Granger Causality and VAR Model Analysis, it suggested the forecasting reference materials for the total amount of cadastral survey general work load. The main result is that the derive of the environment variables which affect cadastral survey general work load and the outcome of VAR(vector auto regression) analysis materials(impulse response function and forecast error variance decomposition analysis materials), which explain the change of general work load depending on altering the environment variables. And also, For confirming the stability of time series data, we took a unit root test, ADF(Augmented Dickey-Fuller) analysis and the time series model analysis derives the best cadastral forecasting model regarding on general cadastral survey work load. And also, it showed up the various standards that are applied the statistical method of econometric analysis so it enhanced the prior aggregate system of cadastral survey work load forecasting.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.321-328
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• 2000

Working day variations caused by trading days, holidays and leap year make it difficult to analyze monthly or quarterly economic time series. In this paper, we adjust working day variations from economic time series via RegARIMA model.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1133-1140
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• 2008

The goal of this paper is to analysis of the trend for stream quality in Gumi industrial complex with Winters' exponential smoothing method. It used the five different monthly time series data such as BOD, COD, TN, TP and EC from January 1998 to December 2006. The data of BOD, COD, TN, TP and EC are analyzed by time series method and forecasted the trends until December 2007. The stream qualities change for the better about BOD, COD, TN and TP, but the stream qualities resulted by EC is still serious.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2009.04a
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• pp.243-246
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• 2009

Housing distribution rate in our country has been continuously increased with economic growth, but residential plans satisfying the demands of residents are still not perfect yet. The demands of residents can be predicted by analyzing the housing viewpoint of residents. And also, the housing viewpoint can change according to various environmental changes, so it's important for us to understand the trend of change. Therefore, the housing viewpoints of university students who will be subjective residents of houses in future were analyzed by observing change due to trend of time. Target for this study is female university students in 20s. A portion of previously presented material (Korean Home Economics Association 37,1, 67-78) was used as data for 1998 and a questionnaire with 171 female university students was conducted on December 2008 for data for 2008. The following result was drawn from examination of change in the housing viewpoint due to trend of time by comparing the housing viewpoint of university students between 1998 and 2008. First, importance of was decreased and importance of was increased in functions of residence. Second, Most students thought and regardless of the time passage as their opinions on housing. And also, most students considered a living room as the most important space inside of a house regardless of the time passage and the ratio of considering a living room as the most important space was more increased.

• The Korean Journal of Applied Statistics
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• v.19 no.2
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• pp.369-377
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• 2006

This paper considers moving variance ratio (MVR) for valiance detection problem with time series data in progress. For testing purpose, parametric method based on F distribution and nonparametric method based on empirical distribution are compared via simulation study.

• Journal of the Korean Society of Costume
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• v.53 no.8
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• pp.53-63
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• 2003

Under the social conditions that an understanding of a men change socially and men's interests in their appearances are on the increase, this research intends to study and analyze the changes of people's sensibility of values on ads for men's cosmetics, which is said to be performed the social, cultural function reflecting the social consciousness, the value and the idea creating a new one. The documents for the research was sindonga. The documents were analyzed quantitatively in regard of contents of a linguistic expression and a visual expression showing on advertisements for man's cosmetics, a time series analysis. As a result of analyzing the consumption value through headline of an ad, the emotional value took the highest percentage extending whole periods. Beside emotional value, a time series analysis showed that social values appeared to the major themes in the 1970s, and functional values was important themes in 1980s, and the social values and functional values appeared equally during 1990-2002.

• 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.

• Journal of Korean Society for Quality Management
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• v.26 no.1
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• pp.126-142
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• 1998

Traditional statistical process control(SPC) assumes that consective observations from a process are independent. In industrial practice, however, observations are ofter serially correlated. A common a, pp.oach to building control charts for autocorrelatd data is to a, pp.y classical SPC to the residuals from a time series model fitted. Unfortunately, one cannot completely escape the effects of autocorrelation by using charts based on residuals of time series model. For the detection of variance change in the process we propose a CUSUM of squares control chart which does not require the model identification. The proposed CUSUM of squares chart and the conventional control charts are compared by a Monte Carlo simulation. It is shown that the CUSUM of squares chart is more effective in the presence of dependency in the processes.