Unlock instant, AI-driven research and patent intelligence for your innovation.

Ship static data supplement method and device, electronic equipment and readable storage medium

A static data and ship technology, applied in the computer field, can solve the problems of low data accuracy, low supplementary accuracy, and inability to make full use of it

Active Publication Date: 2022-03-08
亿海蓝(北京)数据技术股份公司
View PDF9 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Using the mean value for supplementation will lead to low accuracy of the supplementary data
The univariate regression method cannot make full use of other information in the AIS data, which will also lead to low supplementary accuracy

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 static data supplement method and device, electronic equipment and readable storage medium
  • Ship static data supplement method and device, electronic equipment and readable storage medium
  • Ship static data supplement method and device, electronic equipment and readable storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0052] like figure 1 As shown, this embodiment provides a method for supplementing ship static data, including the following steps:

[0053] Step S102, obtaining a sample ship set, where the sample ship set includes a ship set with complete ship static information and ship historical track data;

[0054] Step S104, processing the sample ship set to obtain sample feature data;

[0055] Step S106, building a feature validity judgment model based on the sample feature data;

[0056] Step S108, using the feature validity judgment model to judge the validity of the sample feature data, and replacing the invalid data with the first valid value to obtain the first data;

[0057] Step S110, constructing a supplementary model of static data by using the first data;

[0058] Step S112, acquiring target ship information, the target ship information includes target ship static information and target ship historical track data;

[0059] Step S114, processing the target ship information...

Embodiment 2

[0073] like figure 2 As shown, this embodiment provides a method for supplementing ship static data. In addition to the technical features of the above-mentioned embodiments, this embodiment further includes the following technical features:

[0074] The sample ship set is processed to obtain sample characteristic data, which specifically includes the following steps:

[0075] Step S202, using the target variable encoding method to encode the category feature;

[0076] Step S204, processing the ship's historical trajectory data to generate trajectory features.

[0077] In this embodiment, the acquired sample ship set is processed based on the business background to form a feature set adapted to the machine learning model, that is, sample feature data.

[0078]This embodiment can be implemented through feature engineering, and the feature engineering includes using the target variable encoding method to encode category features and process historical ship track data to gener...

Embodiment 3

[0080] like image 3 As shown, this embodiment provides a method for supplementing ship static data. In addition to the technical features of the above-mentioned embodiments, this embodiment further includes the following technical features:

[0081] Based on the sample feature data, construct a feature validity judgment model, which includes the following steps:

[0082] Step S302 , based on the sample feature data, a semi-supervised anomaly detection algorithm is used to construct a feature validity judgment model.

[0083] In this embodiment, a semi-supervised method is used to construct a feature validity judgment model through an anomaly detection algorithm, and the feature validity judgment model can effectively identify whether the feature variable value is an invalid value, improve the recognition accuracy, and then make the supplementary ship The data accuracy rate of static data is increased.

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 provides a ship static data supplement method and device, electronic equipment and a readable storage medium. The ship static data supplement method includes: obtaining a sample ship set; obtaining sample feature data; constructing a feature validity judgment model; using a feature validity judgment model to judge the validity of sample feature data; constructing a static data supplementary model; obtaining target ship information; Obtain the target feature data; use the feature validity judgment model to judge the validity of the target feature data, and replace the invalid data with the second effective value to obtain the second data; input the second data into the static data supplement model, and the target The static information of the ship is supplemented with static data, and the complete static information of the target ship is obtained. The invention can improve the accuracy of the supplementary data of the static information of the target ship.

Description

technical field [0001] The present invention relates to the field of computer technology, and in particular, to a method and device for supplementing static data of ships, an electronic device and a readable storage medium. Background technique [0002] Supplementing the ship's static data in the related art usually adopts mean value supplementation, or learns the univariate regression relationship between the static features and the ship length that needs to be supplemented, and uses the regression function to supplement. Complementing with the mean will result in a low accuracy rate of the supplemented data. The method of univariate regression cannot make full use of other information in the AIS data, and it will also lead to the situation that the supplementary accuracy is too low. SUMMARY OF THE INVENTION [0003] The present invention aims to solve or improve at least one of the above technical problems. [0004] Therefore, the first object of the present invention ...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/21G06F16/23G06K9/62
CPCG06F16/219G06F16/2365G06F18/24323
Inventor 邢璐韩斌
Owner 亿海蓝(北京)数据技术股份公司