Ship trajectory classification method based on feature selection and hyper-parameter optimization

A ship trajectory and feature selection technology, applied in special data processing applications, geographic information databases, structured data retrieval, etc., can solve the problem of no combination of dynamic and static features, no classification of multiple ship trajectories, no solution to AIS, etc. problem, achieve accurate and reliable classification results, facilitate machine learning, and overcome imbalance problems

Active Publication Date: 2021-08-10
SICHUAN UNIV
View PDF12 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, these studies only classify the trajectories of ships into specific ship operations, and do not classify the trajectories of various ships, nor combine dynamic features such as

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Ship trajectory classification method based on feature selection and hyper-parameter optimization
  • Ship trajectory classification method based on feature selection and hyper-parameter optimization
  • Ship trajectory classification method based on feature selection and hyper-parameter optimization

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0070] In order to make the above objects, features and advantages of the present invention more clearly understood, the present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.

[0071] like figure 1 As shown, a flow chart of the steps of a ship trajectory classification method based on feature selection and hyperparameter optimization of the present invention is shown, and the method may specifically include the following steps:

[0072] The first step is to prepare the nautical trajectory data, perform data cleaning and preprocessing on the nautical trajectory data, and obtain the candidate data of the nautical trajectory data:

[0073] The automatic identification system (AIS) data used in the example of the present invention is a new generation marine communication and navigation system operating in the VHF band. AIS messages provide a wealth of vessel information, mainly including dynamic informati...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a ship trajectory classification method based on feature selection and hyper-parameter optimization. For the problem of unbalanced original data in ship trajectory classification, firstly, data cleaning and preprocessing are performed on multiple pieces of trajectory data of an automatic ship identification system, then all trajectories are drawn by matplotlib, unavailable trajectories are deleted, then features are calculated to obtain additional features, dimensionality reduction processing is performed on speed, course and trajectory coordinates, backward feature selection is carried out on all features after dimension reduction processing through a random forest (RF), finally hyper-parameter optimization is carried out through the random forest, and classification prediction is carried out on the features through model training and performance evaluation without depending on an external information source. The ship trajectory classification method has high performance and is stable, and can be effectively applied to actual ship trajectory classification.

Description

technical field [0001] The invention relates to trajectory classification technology, in particular to a ship trajectory classification method based on feature selection and hyperparameter optimization. Background technique [0002] With the rapid development of maritime satellite navigation and positioning technology, the safety and efficiency of maritime transportation has become very important. The number of ships in global ocean transportation has reached an unprecedented level, and it is showing a trend of high-speed, large-scale and intelligent development. In 2021 The unexpected congestion and closure of the Suez Canal in March, rising tensions in the freight market, and the associated economic impacts are beginning to emerge show the value of trajectory classification. The automatic identification system (Automatic Identification System, AIS) is a new generation of maritime communication and navigation system working in the VHF band. The AIS message provides a wealth...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F16/215G06F16/2458G06F16/29G06K9/62
CPCG06F16/215G06F16/2465G06F16/29G06F18/24323
Inventor 温婷婷时宏伟
Owner SICHUAN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products