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A ship type counterfeiting detection method based on ensemble learning

An integrated learning and ship technology, applied in the field of ship type counterfeiting monitoring based on integrated learning, can solve the problems of aggravating the safety hazards of water transportation, increasing the difficulty of supervision by the maritime department, and the low accuracy rate, so as to improve efficiency, solve poor efficiency, The effect of fast monitoring speed

Active Publication Date: 2020-05-19
NANJING LES CYBERSECURITY & INFORMATION TECH RES INST CO LTD
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  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

The counterfeiting of AIS types, mainly fishing boats, has undoubtedly greatly increased the difficulty of supervision by the maritime department and aggravated the safety hazards of water transportation
In the face of counterfeiting of ship types, traditional maritime supervision methods can only estimate the position, speed, course and other information in the ship’s AIS message based on experience. This method is not only extremely inefficient, but also often inaccurate

Method used

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  • A ship type counterfeiting detection method based on ensemble learning
  • A ship type counterfeiting detection method based on ensemble learning
  • A ship type counterfeiting detection method based on ensemble learning

Examples

Experimental program
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Effect test

Embodiment Construction

[0047] Such as figure 1 As shown, a method for monitoring counterfeiting of ship types based on integrated learning includes the following steps:

[0048] (1) Cleaning and classification of ship historical track data;

[0049] (11) Set rules to clean historical data

[0050] Such as figure 2 As shown, first set the cleaning rules, including but not limited to the location should be in the area of ​​responsibility and cannot be on land, the speed cannot be negative, the heading and heading cannot be negative and cannot be greater than 360 degrees, the position and speed in the historical data , Course and other data items comply with the outlier point cleaning rules to remove the track points;

[0051] (12) Deduplication of historical data

[0052] Traverse the data, remove track points with the same time, position, and heading as duplicate points to prevent them from affecting the statistical results;

[0053] (13) Make data type adjustments

[0054] For some ship types named with char...

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Abstract

The invention provides a ship type counterfeiting monitoring method based on integrated learning, including a method for cleaning historical ship data and type adjustment; feature selection, format transformation and sliding window feature generation method, feature normalization method; classification The selection and composition of the classifier, the setting method of the classifier evaluation function; the real-time ship target type judgment and monitoring method. The invention can use historical ship track messages to train and generate a model for ship type judgment and monitoring, and can perform type judgment and monitoring on real-time ship targets, and alarm suspected counterfeit targets, helping the maritime department to find counterfeit ships in time Target.

Description

Technical field [0001] The invention relates to a ship type monitoring method, in particular to a ship type counterfeiting monitoring method based on integrated learning Background technique [0002] With the development of my country's water production activities, the number of ships navigating in major ports and waterways is increasing. More and more ships also bring higher and higher risks of navigation accidents. The counterfeiting of the AIS type mainly by fishing boats has undoubtedly greatly increased the difficulty of supervision by the maritime department and increased the safety hazards of water transportation. In the face of counterfeiting of ship types, traditional maritime supervision methods can only estimate the position, speed, heading and other information in the ship’s AIS message based on experience. This method is not only extremely inefficient, but also often not accurate. Early and better detection of types of counterfeiting violations can effectively redu...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/33G06F16/35G06K9/62G06N20/20
CPCG06F16/334G06F16/355G06N20/20G06F18/24323
Inventor 段然隋远沈昌力王维圳白正
Owner NANJING LES CYBERSECURITY & INFORMATION TECH RES INST CO LTD
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