• Journal of Korean Society of Coastal and Ocean Engineers
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• v.22 no.3
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• pp.163-170
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• 2010

Both scatterer method and transfer matrix method are compared to analyze their characteristics, which are wave propagation models due to topographic change based on plane wave approximation. Results from the scatterer method are closer to the results obtained by the more accurate existing models and it is appraised that the scatterer method gives the clearer explanation about physical process involved in the wave transformation. Since both methods have analytical solutions, in the computational point of view they are very fast and easy to be implemented. Both methods give a good prediction for wave scattering by relatively simple bedform.

• The Korean Journal of Applied Statistics
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• v.20 no.2
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• pp.373-385
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• 2007

The solution of the normal equation arising in a general linear model by the least square methods is not unique in general. Conventionally, SAS IML and G-inverse matrices are considered for such problems. In this paper, we provide a systematic solution procedures for SAS IML.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10a
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• pp.537-541
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• 2006

최근 특정 주제의 지적 구조를 파악하기 위한 저자 동시인용분석, 동시단어분석, 서지결합법 등 계량정보분석에 대한 연구가 활발히 진행되고 있다. 그러나 국내의 경우 계량정보분석 기법을 활용한 정보 유통 프레임웍을 갖추고 있는 연구기관이나 대학이 아직 없는 실정이다. 그 이유는 특허나 과학문헌에 대한 인용정보를 보유한 곳이 없고, 거대 인용정보 행렬을 계산하기 위한 컴퓨팅 자원을 확보하지 못하고 있기 때문이다. 본 연구는 미국 특허 데이터베이스를 대상으로 인용 피인용 행렬을 생성한 후, 클러스터 컴퓨터를 사용하여 동시인용과 서지결합빈도를 계산하고 그 결과를 이용자에게 제공하는 정보 유통 서비스 모델을 제시하고자 한다.

• The Korean Journal of Applied Statistics
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• v.24 no.2
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• pp.373-381
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• 2011

This paper discusses how to get the sums of squares due to treatment factors when Type I Analysis is used by projections for the analysis of data under the assumption of a two-way ANOVA model. The suggested method does not need to calculate the residual sums of squares for the calculation of sums of squares. There-fore, the calculation is easier and faster than classical ANOVA methods. It also discusses how eigenvectors and eigenvalues of the projection matrices can be used to get the calculation of sums of squares. An example is given to illustrate the calculation procedure by projections for unbalanced data.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.7 no.5
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• pp.180-183
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• 2008

This research addresses the problem of estimating Origin-Destination (O-D) trip matrices from link volume counts, a set of unobserved link volumes and information of user equilibrium flows in transportation networks. A heuristic algorithm for estimating unobserved link flows is derived, which provides volume estimates that are approximately consistent with both observed flows and an assumption of user equilibrium conditions. These estimated link volumes improve the constraints associated with the synthetic OD estimation model, providing improved solution search procedure. Model performance is tracked in terms of the root mean square errors (RMSE) in predicted travel demands, and where appropriate, predicted linked volumes. These results indicate that the new model substantially outperforms existing approaches to estimating user-equilibrium based synthetic O-D matrices.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.11-20
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• 2017

In this paper, we introduced linear spatial time series (space-time autoregressive and moving average model) and nonlinear spatial time series (space-time bilinear model). Also we estimated the parameters by Kalman Filter method and made comparative studies of power of forecast in the final model. We proposed several weight matrices such as equal proportion allocation, reciprocal proportion between distances, and proportion of population sizes. For applications, we collected Mumps data at Korea Center for Disease Control and Prevention from January 2001 until August 2008. We compared three approaches of weight matrices using the Mumps data. Finally, we also decided the most effective model based on sum of square forecast error.

• Science & Technology Policy
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• v.16 no.1 s.157
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• pp.90-100
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• 2006

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.19-32
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• 2018

This study focuses on an M/M/1 queue with an attached continuous-type inventory. The customers arrive into the system according to the Poisson process, and are served in their arrival order; i.e., first-come-first-served. The service times are assumed to be independent and identically distributed exponential random variable. At a service completion epoch, the customer consumes a random amount of inventory. The inventory is controlled by the traditional (s, S)-inventory policy with a generally distributed lead time. A customer that arrives during a stock-out period assumed to be lost. For the number of customers and the inventory size, we derive a product-form stationary joint probability distribution and provide some numerical examples. Besides, an operational strategy for the inventory that minimizes the long-term cost will also be discussed.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.26-36
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• 2021

In this study, a deep learning model for predicting the queue length was developed using the information collected from the image detector. Then, a multiple regression analysis model, a statistical technique, was derived and compared using two indices of mean absolute error(MAE) and root mean square error(RMSE). From the results of multiple regression analysis, time, day of the week, occupancy, and bus traffic were found to be statistically significant variables. Occupancy showed the most strong impact on the queue length among the variables. For the optimal deep learning model, 4 hidden layers and 6 lookback were determined, and MAE and RMSE were 6.34 and 8.99. As a result of evaluating the two models, the MAE of the multiple regression model and the deep learning model were 13.65 and 6.44, respectively, and the RMSE were 19.10 and 9.11, respectively. The deep learning model reduced the MAE by 52.8% and the RMSE by 52.3% compared to the multiple regression model.

• Journal of Korean Society of Transportation
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• v.17 no.2
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• pp.179-191
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• 1999

To device effective freeway traffic flow control strategies and freeway traffic information dissemination strategies, it is very important to estimate real physical queue length on the freeway. Shock wave theory and queueing theory have limitation to be used to estimate the queue length. The primary objective of this study is to develop a reliable method for estimating the physical queue length and level of congestion. Queueing propagation processes were analysed by using such traffic data as main line traffic volume, ramp volume, density. speed, and physical queue length collected by video photographing on Olympic Freeway. As a result of analysis, it has been confirmed that the real queue length can be estimated by using the traffic counts arriving the congested region and passing a bottleneck location. Further more, a reliable method for estimating the level of congestion could be developed on the basis of real-time traffic counts.