130   Artículos

 
en línea
Haoran Liu, Kehui Xu, Bin Li, Ya Han and Guandong Li    
Machine learning classifiers have been rarely used for the identification of seafloor sediment types in the rapidly changing dredge pits for coastal restoration. Our study uses multiple machine learning classifiers to identify the sediment types of the C... ver más
Revista: Water    Formato: Electrónico

 
en línea
Yang Liu, Qiang Zhang, Longjin Wang, Shun An, Yan He, Zhimin Fan and Fang Deng    
This paper investigates the problem of real-time parameter identification for ship maneuvering parameters and wave peak frequency in an ocean environment. Based on the idea of Euler discretion, a combined model of ship maneuvering and wave peak frequency... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Jin Pan, Yong Wang, Tao Wang and Mingcai Xu    
With the development of bridge crossings over rivers, the accident of the vessel?bridge collision is increasing as well. It is important to assess probability of bridges colliding with passing ships. Firstly, the AIS (Automatic identify system) data was ... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
João N. Ribeiro da Silva, Tiago A. Santos and Angelo P. Teixeira    
This paper develops a methodology to estimate ship emissions using Automatic Identification System data (AIS). The methodology includes methods for AIS message decoding and ship emission estimation based on the ship?s technical and operational characteri... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
José Miguel Rodrigues    
The timely and precise prediction of flooding progression and its eventual outcome in ships with breached hulls can lead to dramatic improvements in maritime safety through improved guidance for both emergency response and ship design. The traditional ap... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Ye Xiao, Yupeng Hu, Jizhao Liu, Yi Xiao and Qianzhen Liu    
Ship trajectory prediction is essential for ensuring safe route planning and to have advanced warning of the dangers at sea. With the development of deep learning, most of the current research has explored advanced prediction methods based on historical ... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Yao Meng, Xianku Zhang, Guoqing Zhang, Xiufeng Zhang and Yating Duan    
In order to establish a sparse and accurate ship motion prediction model, a novel Bayesian probability prediction model based on relevance vector machine (RVM) was proposed for nonparametric modeling. The sparsity, effectiveness, and generalization of RV... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Cheor-Hong Park, Bong-Kyu Jung and Won-Sam Choi    
Fishing boats are equipped to quickly rescue ships and save lives in the event of an incident at sea; therefore, determination of the incident location is imperative for a swift response. According to the 2021 marine accidents by ship use statistics, fis... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Shanshan Chen, Sheng Guan, Hui Wang, Ningqi Ye and Zexun Wei    
Ship type identification is an important basis for ship management and monitoring. The paper proposed a new method of ship type identification by combining characteristic parameters from the energy difference between high and low frequencies and the sens... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

 
en línea
Zhaojin Yan, Guanghao Yang, Rong He, Hui Yang, Hui Ci and Ran Wang    
Automatic identification systems (AIS) provides massive ship trajectory data for maritime traffic management, route planning, and other research. In order to explore the valuable ship traffic characteristics contained implicitly in massive AIS data, a sh... ver más
Revista: Journal of Marine Science and Engineering    Formato: Electrónico

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