• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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• pp.1093-1102
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• 2012

In this paper, we predicted the interest spread using the VAR (vector autoregressive) model. Variables used in the VAR model were selected among 56 domestic and foreign macroeconomic time series through crosscorrelation and Granger causality test. The performance of the VAR model was compared with the univariate time series model, AR (autoregressive) model, in view of MAPE (mean absolute percentage error) and RMSE (root mean square error) of forecasts for the last twelve months.

• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.69-77
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• 2007

This study presents comparison results for pedestrian accident reconstruction models representing the relationship between collision speed and horizontal distance that a body travels while falling and sliding. A set of 49 reliable pedestrian accident cases are applied to compare the existing reconstruction models. In addition, the authors investigate the effects of a set of parameters associated with the effects of the frontal shape of a vehicle on the horizontal distance a pedestrian travels while falling and sliding. It has been revealed that the length of the bumper is the most dominant factor to affect the horizontal distance of pedestrian travel after collision. Further analyses utilizing more accident data need to conducted to develop a more accurate and reliable reconstruction model.