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Automatic collision avoidance algorithm based on improved artificial potential field method
Wang Zongkai,Im Namkyun 한국항해항만학회 2023 한국항해항만학회 학술대회논문집 Vol.2023 No.1
With the development of science and technology, various research on ship collision avoidance has also developed rapidly. The research and development of ship collision avoidance technology has also received high attention from many researchers. This paper proposes a new collision avoidance algorithm for ships based on the artificial force field collision avoidance method. Using the simulation platform, the simulation results show that ships can successfully avoid collision in open water under single ship and multi ship situations, and the research results are relatively ideal.
Construction and verification of nonparameterized ship motion model based on deep neural network
Wang Zongkai,Im Nam-kyun 한국항해항만학회 2022 한국항해항만학회 학술대회논문집 Vol.2022 No.2
A ship’s maneuvering motion model is important in a computer simulation, especially under the trend of intelligent navigation. This model is usually constructed by the hydrodynamic parameters of the ship which are generated by the principles of hydrodynamics. Ship’s motion model is a nonlinear function. By using this function, ships’ motion elements can be calculated, then the ship’s trajectory can be predicted. Deeping neural networks can construct any linear or non-linear equation theoretically if there have enough and sufficient training data. This study constructs some kinds of deep Networks and trains this network by real ship motion data, and chooses the best one of the networks, uses real data to train it, then uses it to predict the ship’s trajectory, getting some conclusions and experiences.
Jifeng Yu,Xinlong Pang,Wenzhao Fu,Jason Hilton,Mingmei Liang,Zongkai Jiang,Xiuli Zhao,Wenyan Qiao,Suo Shi,Diandong Zhang,Huitao Cao,Haibo Jia,Yadong Wang,Xiaoke Hu,Rui Zhang 한국지질과학협의회 2021 Geosciences Journal Vol.25 No.5
The Miocene aged Shanwang Formation from the Shanwang National Geopark in China represents a succession of lacustrine diatomaceous shales containing an abundant and diverse biota with lagerstätte fossilization of soft tissues. To date, the Shanwang Formation has not been investigated for cyclostratigraphy nor has it been dated with high precision methods. Now we use thorium data as a paleoenvironmental and paleoclimatic proxy to conduct a detailed cyclostratigraphic analysis. A new and simple cyclostratigraphic method, Wavelet Scale Series Analysis (WSSA) is developed to recognize Milankovitch cycles. A total of three short eccentricity and fifteen precession cycles are identified; obliquity cycles are not apparent. In the sedimentary succession, the corresponding precession and short eccentricity cycles are 1.17 m and 4.98 m thick respectively, with this verified by Correlation Coefficient (COCO) analysis and Multitaper-Method (MTM) spectral analysis. We estimate the studied interval was deposited over a duration of 0.3 Myr with a depositional rate of c. 5.7 cm/kyr. Paleomagnetic and radio isotope dating data shows that the diatomaceous shale was deposited during Chron C5En, which places it at approximately 18.5 Ma during the Burdigalian stage of the Early Miocene, rather than in the Middle Miocene as previously thought. The Shanwang lagerstätte biota therefore predates the Middle Miocene Climate Optimum (MMCO) and did not form within it. The geological time scale with a high resolution of 20 kyr was set accordingly.