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Extraction of Key Factors of Ship Following Behavior based on Rough Set Theory

Author

Listed:
  • Bo Tu

    (Shanghai Maritime University, China)

  • Yihua Liu

    (Shanghai Maritime University, China)

  • Xinyue Li

    (Shanghai Maritime University, China)

  • Shiyu Tu

    (Shanghai Maritime University, China)

Abstract

In order to clarify the main influencing factors of ship following behavior, an algorithm for extracting key factors of ship following behavior based on ship AIS data in straight channel waters is proposed. After the statistical analysis of the obtained ship following trajectory data, the correlation of each influencing factor of ship following behavior and the importance of their influence on the ship following distance are analyzed by applying the rough set dependency and importance assignment methods, and the attribute simplification algorithm based on the rough set dependency and the decision rule algorithm based on the rough set attribute simplification are used to mine the strong correlation rules between each influencing factor and the following distance. Finally, set the straight section of the south channel of the Yangtze River estuary as the study water for case study. The results show that the average ship speed is 9.41 knots, the average space of ship is 2110 m, the average bow time is 450s, and the average relative speed is 0 knot; the weights of ship speed, ship length, relative speed, ship type, density and pilot class in the factors affecting ship following behavior are 0.1953, 0.0836, 0.2092, 0.2265, 0.1852 and 0.1058, respectively; the correlation between ship speed and relative speed is large, no strong correlation rule was found with others; ship following behavior should focus on ship speed and density, and the distance of [1000, 2000 m) is the key concern interval.

Suggested Citation

  • Bo Tu & Yihua Liu & Xinyue Li & Shiyu Tu, 2022. "Extraction of Key Factors of Ship Following Behavior based on Rough Set Theory," European Journal of Engineering and Technology Research, European Open Science, vol. 7(3), pages 55-62, May.
  • Handle: RePEc:epw:ejeng0:v:7:y:2022:i:3:id:62804
    DOI: 10.24018/ejeng.2022.7.3.2804
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