• Nuclear Engineering and Technology
• /
• v.17 no.3
• /
• pp.224-230
• /
• 1985

• Nuclear Engineering and Technology
• /
• v.19 no.1
• /
• pp.55-64
• /
• 1987

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.36 no.3
• /
• pp.521-528
• /
• 2016

The tollbooths of a main motorway toll plaza are usually operated proactively responding to the variations of traffic demands of two-type vehicles, i.e. cars and the other (heavy) vehicles, respectively. In this vein, it is one of key elements to forecast accurate traffic volumes for the two vehicle types in advanced tollgate operation. Unfortunately, it is not easy for existing univariate short-term prediction techniques to simultaneously generate the two-vehicle-type traffic demands in literature. These practical and academic backgrounds make it one of attractive research topics in Intelligent Transportation System (ITS) forecasting area to forecast the future traffic volumes of the two-type vehicles at an acceptable level of accuracy. In order to address the shortcomings of univariate short-term prediction techniques, a Multiple In-and-Out (MIO) forecasting model to simultaneously generate the two-type traffic volumes is introduced in this article. The MIO model based on a non-parametric approach is devised under the on-line access conditions of large-scale historical data. In a feasible test with actual data, the proposed model outperformed Kalman filtering, one of a widely-used univariate models, in terms of prediction accuracy in spite of multivariate prediction scheme.

• Journal of Korean Society of Transportation
• /
• v.25 no.1 s.94
• /
• pp.109-119
• /
• 2007

Increasingly, the emphasis in regional Passenger rail Planning is finding ways to more efficiently use existing facilities, with particular attention being Paid to Policies designed to spread Peak-Period travel demand more evenly throughout the week with consideration of train classification. In this context the individual's choice of time to travel is of crucial significance. This paper investigates the use of multinomial logit analysis to model ridership by rail classification using data collected for travel from Seoul to Busan during the one week in October 2004. The Particular model form that was successfully calibrated was the multinomial logit (MNL) model : it describes the choice mechanism that will Permit rail systems and operations to be planned on a more reliable basis. The assumption of independently and identically distributed(IID) error terms in the MNL model leads to its infamous independence from irrelevant alternatives (IIA) property. Relaxation of the IID assumption has been undertaken along a number or isolated dimensions leading to the development of the MNL model. For business and related rail travel patterns, the most important variables of choice were time and frequency to the chosen destination. The calibrated model showed high agreement between observed and Predicted market shares. The model is expected to be of use to railroad authorities in Planning and determining business strategies in the Increasingly competitive environment or regional rail transport.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2016.07a
• /
• pp.101-102
• /
• 2016

본 논문에서는 차량의 특징점들 사이의 간격과 크기의 비례식으로 자동차의 차종을 식별하는 방법을 제시한다. 자동차 관련 영상은 그 편의성을 위하여 기본 RGB모델에서 Gray색상 모델로 변환시켜 사용한다. 자동차의 배경 제거는 Canny Edge Direction을 통하여 수행하고 외곽선 검을을 통하여 원하는 특징 점을 얻는다.

• Nuclear Engineering and Technology
• /
• v.8 no.3
• /
• pp.167-177
• /
• 1976

• JOURNAL OF ELECTRICAL WORLD
• /
• no.1 s.37
• /
• pp.20-26
• /
• 1980

• Nuclear industry
• /
• no.6
• /
• pp.4-6
• /
• 1979

• The tire
• /
• s.160
• /
• pp.25-33
• /
• 1992

• The Korea Swine Journal
• /
• v.16 no.2 s.174
• /
• pp.148-150
• /
• 1994