Risk ship detection method based on multi-source heterogeneous data fusion

Abstract

The invention discloses a risk ship detection method based on multi-source heterogeneous data fusion, and the method comprises the following steps: 1, building a model, obtaining all historical data of the navigation of ships in different sea areas as a sample for building the model, 2, simplifying a ship navigation traffic system, 3, carrying out the global risk recognition, carrying out modeling on the navigation state of each ship on a sea area by utilizing a GMM (Gaussian Mixture Model), 4, predicting risks, and forming time sequence data by global system collision risk values in different time periods, 5, fusing data information, 6, carrying out data simulation, and 7, carrying out abnormal risk analysis. According to the risk ship detection method, complementarity and comprehensiveness among multi-source information are fully utilized through an information fusion technology, the credibility of ship collision risk assessment is greatly improved, scientific decision making of a ship traffic system is facilitated, and macroscopic cognition and global mastering of main accident risks objectively existing in the ship traffic system are achieved.

Description

technical field [0001] The invention relates to the technical field of ship risk detection, in particular to a risk ship detection method based on multi-source heterogeneous data fusion. Background technique [0002] Ship risk assessment is to determine the key factors that can reflect the risk level through systematic analysis and screening of various factors that affect ship safety, establish a risk assessment index system, and use qualitative or quantitative models to judge each index. The risk value of the overall risk level is used to provide decision support for ship safety management. The establishment of the risk evaluation index system is generally considered from the four elements of man, machine, environment and management. During the operation of the ship, the ship, cargo, Indicators that affect ship risk, such as crew, passengers, waterways and ports, routes, and shipping companies, can be included in the four elements of the ship safety management system: man, ...

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Problems solved by technology

[0003] In the context of intelligent transportation, the risk assessment models proposed in many studies still have their limitations. For example, based on AIS data, a method that can assess the risk level of collisions between encountering ships through navigation data is proposed. To a certain extent, the model It can reasonably assess the collision risk level of the encountering ships, but there is also an unreasonable phenomenon of

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