Prediction of Marine Traffic Density Using Different Time Series Model From AIS data of Port Klang and Straits of Malacca

Ramin, Akim; Mustaffa, M.; Ahmad, Suriati

doi:10.7225/toms.v09.n02.006

Cited by 11 publications

(7 citation statements)

References 9 publications

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“…Although there is no LNG ship traffic in the Bosporus Strait, this simulation procedure is a good reference for the present study. Ramin et al [25] investigated the ship traffic density at Port Klang and in the Straits of Malacca. The exponential smoothing method was proposed to predict the future traffic density, and it achieved satisfactory precision.…”

Section: Literature Reviewmentioning

confidence: 99%

A Simulation Model of the Influence of LNG Ships on Traffic Efficiency at Tianjin Port

Li,

Tian,

Meng

et al. 2024

JMSE

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Tianjin Port is one of the largest ports in northern China. Liquefied natural gas (LNG) ships are one of the most special ship types, and their navigation safety and efficiency has become the top concern of the port authority. There are two LNG berths at the port, and the annual arrivals, which reach more than 100, increasingly influence other ships. The objective of this study is to evaluate the influence of LNG ships on other ships in a quantitative way. To realize this, a simulation system is established by analyzing the factors affecting waterway transit efficiency. The software Arena is adopted to simulate the arrival and departure of the ships at Tianjin Port and to simulate how the average waiting time and the average queue length in the port area are affected by the LNG ships. A traffic system for the two ship types is formulated, and the mutual influences between them are expressed by the inbound and outbound waterway states. The simulations are performed under both existing and new ship traffic regulations. Cases in which the number of LNG ships gradually increases are simulated comprehensively. The simulation model as well as the results can serve as a good reference for the local port authority in the formulation of traffic regulations.

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Section: Literature Reviewmentioning

confidence: 99%

A Simulation Model of the Influence of LNG Ships on Traffic Efficiency at Tianjin Port

Li,

Tian,

Meng

et al. 2024

JMSE

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“…Son et al [17] proposed a method that predicted maritime traffic congestion by combining the automatic identification systems of ships and port management information data. Ramin et al [18] used timeseries models and the associative models to predict the maritime traffic density of Port Klang and the Straits of Malacca. For the prediction of maritime traffic flow, Zhou et al [19] used deep learning solutions such as CNN, LSTM, and BDLSTM-CNN.…”

Section: Related Workmentioning

confidence: 99%

An Efficient Feature Augmentation and LSTM-Based Method to Predict Maritime Traffic Conditions

Lee

Khan

Son³

et al. 2023

Applied Sciences

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The recent emergence of futuristic ships is the result of advances in information and communication technology, big data, and artificial intelligence. They are generally autonomous, which has the potential to significantly improve safety and drastically reduce operating costs. However, the commercialization of Maritime Autonomous Surface Ships requires the development of appropriate technologies, including intelligent navigation systems, which involves the identification of the current maritime traffic conditions and the prediction of future maritime traffic conditions. This study aims to develop an algorithm that predicts future maritime traffic conditions using historical data, with the goal of enhancing the performance of autonomous ships. Using several datasets, we trained and validated an artificial intelligence model using long short-term memory and evaluated the performance by considering several features such as the maritime traffic volume, maritime traffic congestion fluctuation range, fluctuation rate, etc. The algorithm was able to identify features for predicting maritime traffic conditions. The obtained results indicated that the highest performance of the model with a valid loss of 0.0835 was observed under the scenario with all trends and predictions. The maximum values for 3, 6, 12, and 24 days and the congestion of the gate lines around the analysis point showed a significant effect on performance. The results of this study can be used to improve the performance of situation recognition systems in autonomous ships and can be applied to maritime traffic condition recognition technology for coastal ships that navigate more complex sea routes compared to ships navigating the ocean.

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“…In Bužančić Primorac and Parunov (2016), the dynamics of the main types of accidents in shipping were revealed and General Cargo, Bulk Carriers, Passenger and Fishing vessels were found to have the highest accident rates. An analysis and models of accidents in specific shipping lanes in terms of their specifics are presented in Kim et al, (2011), Mou et al, (2015 and Ramin et al, (2020). Particularly, in Kim et al (2011) the results of probabilistic analysis are given for Mokpo waterways and in Mou et al, (2015) for Shenzhen Waters.…”

Section: Literature Overview and Problem Formulationmentioning

confidence: 99%

“…Particularly, in Kim et al (2011) the results of probabilistic analysis are given for Mokpo waterways and in Mou et al, (2015) for Shenzhen Waters. In Ramin et al, (2020) risk prediction models based on time series analysis are presented for Port Klang and the Straits of Malacca. An evaluation of ship performance under varying operational conditions and ship operational efficiency were reviewed in papers (Perera et al, 2015;Aldou, 2015).…”

Section: Literature Overview and Problem Formulationmentioning

confidence: 99%

Assessment of Potential Negative Impact of the System of Factors on the Ship's Operational Condition During Transportation of Oversized and Heavy Cargoes

2021

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The potential risks to vessels and crew in merchant shipping stem from human error, vulnerability to environmental influences, failure of shipboard systems and equipment. In case of transportation of heavy and oversized cargo, the preceding list can be expanded to include potential hazards directly associated with the cargo. This study identified a system of potential negative events in the transportation of oversized and heavy cargo under the influence of multiple factors. Negative events are divided into two categories: those occurring during loading/unloading and those occurring during transportation. The consequences of these negative events for cargo and operational condition of the ship are also identified. Six basic options for the operational condition of the vessel in the transportation process of oversized and heavy cargo have been determined. The conceptual model of the combination of factors affecting the operational condition of the vessel during the transportation of oversized and heavy cargo is formulated, and the chain of formation of the probability of negative events during the transportation of oversized and heavy cargo is identified and mathematically described. A basic pattern of relationship between various negative events occurring during transportation of oversized and heavy cargoes and ship's operational conditions is established. The obtained results allow the probability of possible negative events and change of ship's condition due to such influences during the transportation of the cargo category concerned to be estimated in practice, taking into account the specifics of a particular port, vessel and shipping line.

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Prediction of Marine Traffic Density Using Different Time Series Model From AIS data of Port Klang and Straits of Malacca

Cited by 11 publications

References 9 publications

A Simulation Model of the Influence of LNG Ships on Traffic Efficiency at Tianjin Port

A Simulation Model of the Influence of LNG Ships on Traffic Efficiency at Tianjin Port

An Efficient Feature Augmentation and LSTM-Based Method to Predict Maritime Traffic Conditions

Assessment of Potential Negative Impact of the System of Factors on the Ship's Operational Condition During Transportation of Oversized and Heavy Cargoes

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