• 해양환경안전학회지
• /
• 제20권3호
• /
• pp.285-291
• /
• 2014

This study applied regression analysis to evaluate the impact of hourly average congestion calculated by bumper model in the congested area of each passage of each port on the peak time congestion, to suggest the model formula that can predict the peak time congestion. This study conducted regression analysis of hourly average congestion and peak time congestion based on the AIS survey study of 20 ports in Korea. As a result of analysis, it was found that the hourly average congestion has a significant impact on the peak time congestion and the prediction model formula was derived. This formula($C_p=4.457C_a+29.202$) can be used to calculate the peak time congestion based on the predicted hourly average congestion.

• 한국항만경제학회지
• /
• 제33권4호
• /
• pp.135-148
• /
• 2017

본 연구는 다음과 같은 문제를 제기한다. 체선이 항만의 운영 효율성에 어느 정도 영향을 미치는가? 이 연구 문제에 대한 답하기 위해 본 연구에서는 SBM-DEA 모형을 이용하여 체선을 고려한 항만의 효율성을 분석하고 DEA-CCR BCC 모형의 연구 결과와 비교하였다. 먼저 DEA-CCR BCC 분석 결과, 부산(2011), 울산(2011)이 효율적인 DMU로 나타났으며 DEA-BCC 모형 분석 결과, 부산(2011), 울산(2011), 울산(2012), 부산(2012), 여수 광양(2012)이 효율적인 DMU로 나타났다. 체선을 고려한 SBM-DEA 모형 분석 결과, 울산(2012), 부산(2011), 부산(2012), 인천(2011), 울산(2011)이 효율적인 DMU로 나타났다. DEA-CCR BCC 결과와 SBM-DEA 결과 간 불일치를 보여 체선이 항만의 운영 효율성에 미치는 영향이 크지 않은 것으로 나타났으며 체선선박척수의 잔여물을 제거한다면 인천항은 3년간 총 11.9억 원, 여수 광양항은 3년 간 총 65.52억 원의 비용 보존이 가능한 것으로 나타났다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제17권1호
• /
• pp.216-238
• /
• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• 한국항만경제학회지
• /
• 제19권2호
• /
• pp.33-53
• /
• 2003

The purpose of this paper is to investigate the effectiveness of port investemnt which is one of the important elements for measuring the port efficiency by using congestion approach of DEA(Data Envelopment Analysis). Congestion is said to be present when increases in inputs result in input reductions. Congestion approach takes the forms of weak input disposability and strong input disposability. Empirical analysis by using congestion approach in this paper identified inefficiencies in the inputs including port investment, and indicated inefficient ports like the ports of Sokcho, Gunsan, Pohang, and Seoguipo which shows the large amount of slacks with congestion especially in terms of port investment. Therefore these ports should examine the reason about the inefficiency of port investment. The main policy implication based on the findings of this study is that The Ministry of Maritime Affairs & fisheries in Korea should introduce congestion approach when the amount of port investment to each port is decided.

• 한국항만경제학회:학술대회논문집
• /
• 한국항만경제학회 2003년도 정기학술대회지
• /
• pp.221-242
• /
• 2003

The purpose of this paper is to investigate the effectiveness of port investment which is one of the important elements for measuring the port efficiency by using congestion approach of DEA(Data Envelopment Analysis). Congestion is said to be present when increases in inputs result in ouput reductions. Congestion approach takes the forms of weak input disposability and strong input disposability. Empirical analysis by using congestion approach in this paper identified inefficiencies in the inputs including port investment, and indicated inefficient ports like the ports of Sokcho, Gunsan, Pohang, and Seoguipo which shows the large amount of slacks with congestion especially in terms of port investment. Therefore these ports should examine the reason about the inefficiency of port investment. The main policy implication based on the findings of this study is that The Ministry of Maritime Affairs & Fisheries in Korea should introduce congestion approach when the amount of port investment to each port is decided.

• Asia pacific journal of information systems
• /
• 제26권3호
• /
• pp.427-448
• /
• 2016

The stochastic phenomena of traffic network condition, such as traffic speed and density, are affected not only by exogenous traffic control but also by endogenous changes in service time during congestion. In this paper, we propose a mixed M/G/1 queuing model by introducing a condition-varying parameter of traffic congestion to reflect structural changes in the traffic network. We also develop congestion indices to evaluate network efficiency in terms of traffic flow and economic cost in traffic operating system using structure-changing queuing model, and perform scenario analysis according to various traffic network improvement policies. Empirical analysis using Korean highway traffic operating system shows that our suggested model better captures structural changes in the traffic queue. The scenario analysis also shows that occasional reversible lane operation during peak times can be more efficient and feasible than regular lane extension in Korea.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제54권6호
• /
• pp.359-365
• /
• 2005

This paper presents an reduced-order near-optimal controller for the congestion control of Available Bit Rate (ABR) service in Asynchronous Transfer Mode (ATM) networks. We introduce the model, of a class of ABR traffic, that can be controlled using a Explicit Rate feedback for congestion control in ATM networks. Since there are great computational complexities in the class of optimal control problem for the ABR model, the near-optimal controller via reduced-order technique is applied to this model. It is implemented by the help of weakly coupling and singular perturbation theory, and we use bilinear transformation because of its computational convenience. Since the bilinear transformation can convert discrete Riccati equation into continuous Riccati equation, the design problems of optimal congestion control can be reduced. Using weakly coupling and singular perturbation theory, the computation time of Riccati equations can be saved, moreover the real-time congestion control for ATM networks can be possible.

• 한국시스템다이내믹스연구
• /
• 제12권1호
• /
• pp.75-87
• /
• 2011

Congestion problems can be approached from the viewpoint of system dynamics theory. The relationship between road capacity and congestion can be explained by the 'relative control' archetype among four system archetypes suggested by Wolstenholme. There is a balancing feedback loop between road capacity and road congestion. However, there is another balancing loop between road congestion and car traffic volume, which keeps disrupting the equilibrium of the former loop. A system dynamics model, which is based on a partial adjustment model of induced traffic in the literature, is built to simulate three road building scenarios: 'Expanding investment', 'Balancing investment' and 'Frozen road investment' scenarios. The 'Expanding investment' scenario manages to drop congestion levels by 9% over 30 years, however, causing much higher emissions of $CO_2$ than other scenarios. The trade-off relationship between congestion levels and environmental costs must be taken into consideration for road investment policies.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2006년도 추계학술대회 논문집 전력기술부문
• /
• pp.275-278
• /
• 2006

This paper describes a probabilistic annual congestion cost assessment of a grid at a composite power system derived from a model. This probabilistic congestion cost assessment simulation model includes capacity limitation and uncertainties of the generators and transmission lines. In this paper, the proposed probabilistic congestion cost assessment model is focused on an annualized simulation methodology for solving long-term grid expansion planning issues. It emphasizes the questions of "how should the uncertainties of system elements (generators, lines and transformers, etc.) be considered for annual congestion cost assessment from the macro economic view point"? This simulation methodology comes essentially from a probabilistic production cost simulation model of composite power systems. This type of model comes from a nodal equivalent load duration curve based on a new effective load model at load points. The characteristics and effectiveness of this new simulation model are illustrated by several case studies of a test system.

• 한국도로학회논문집
• /
• 제16권4호
• /
• pp.127-134
• /
• 2014

PURPOSES : To operate more efficient traffic management system, it is utmost important to detect the change in congestion level on a freeway segment rapidly and reliably. This study aims to develop classification method of congestion change type. METHODS: This research proposes two classification methods to capture the change of the congestion level on freeway segments using the dedicated short range communication (DSRC) data and the vehicle detection system (VDS) data. For developing the classification methods, the decision tree models were employed in which the independent variable is the change in congestion level and the covariates are the DSRC and VDS data collected from the freeway segments in Korea. RESULTS : The comparison results show that the decision tree model with DSRC data are better than the decision tree model with VDS data. Specifically, the decision tree model using DSRC data with better fits show approximately 95% accuracies. CONCLUSIONS : It is expected that the congestion change type classified using the decision tree models could play an important role in future freeway traffic management strategy.