Ship AIS trajectory clustering method and device based on convolution auto-encoder

A technology of convolutional auto-encoding and trajectory clustering, applied in instruments, character and pattern recognition, relational databases, etc., can solve the problem of wasting computing resources and time, and achieve the effect of avoiding computing deviation and improving computing performance.

Active Publication Date: 2020-09-22
HAINAN UNIVERSITY
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Problems solved by technology

[0005] Traditional trajectory clustering methods usually need to select the spatio-temporal trajectory measurement method according to the amount of relevant data and type of trajectory, computational complexity, noise and

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  • Ship AIS trajectory clustering method and device based on convolution auto-encoder
  • Ship AIS trajectory clustering method and device based on convolution auto-encoder
  • Ship AIS trajectory clustering method and device based on convolution auto-encoder

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[0056] Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with this specification. Rather, they are merely examples of apparatuses and methods consistent with aspects of the present specification as recited in the appended claims.

[0057] The terms used in this specification are for the purpose of describing particular embodiments only, and are not intended to limit the specification. As used in this specification and the appended claims, the singular forms "a", "the", and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It should also be understood that the ter...

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Abstract

The invention relates to a ship AIS trajectory clustering method and device based on a convolution auto-encoder. The ship AIS trajectory clustering method based on a convolutional auto-encoder comprises the following steps: acquiring a continuous trajectory of a ship, and dividing the continuous trajectory into a plurality of sub-trajectories; performing feature engineering extraction on the plurality of sub-trajectories to obtain a sub-trajectory feature matrix; inputting the sub-track feature matrix into a multi-feature fusion auto-encoder to obtain a position feature vector, a speed featurevector and a course feature vector; splicing the position feature vector, the speed feature vector and the course feature vector to obtain a potential feature vector of the ship trajectory; and performing trajectory clustering operation on the extracted ship trajectory feature vector to obtain a ship trajectory clustering result. According to the method, a space-time trajectory measurement methoddoes not need to be selected according to the related data size, trajectory type, calculation complexity, noise and other influence factors, and a similarity distance formula is not needed, so that the calculation time and resources are saved.

Description

technical field [0001] The invention relates to the technical field of software engineering, in particular to a ship AIS track clustering method and device based on a convolutional autoencoder. Background technique [0002] Satellite AIS (Automatic Identification System, ship automatic identification system) is a kind of ship positioning technology. It receives the AIS message information sent by the ship through the low-orbit satellite, and the satellite will receive and decode the AIS message information and forward it to the corresponding earth station, so that Let the land management organization grasp the relevant dynamic information of the ship, and realize the monitoring of the ship sailing in the open sea. [0003] In order to improve the capability and efficiency of ship shipping, the existing technology clusters the ship navigation trajectory information data obtained from the AIS, so that the navigation plan can be predicted according to the clustering results. ...

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Application Information

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IPC IPC(8): G06F16/29G06F16/28G06K9/62
CPCG06F16/29G06F16/285G06F18/23G06F18/22G06F18/253
Inventor 王太正叶春杨周辉
Owner HAINAN UNIVERSITY
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