Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Flight risk behavior identification method based on improved random forest

A random forest and identification method technology, applied in the field of flight risk behavior identification, can solve problems such as no effective methods found, and achieve the effect of improving technical actions

Active Publication Date: 2019-12-03
CIVIL AVIATION UNIV OF CHINA
View PDF8 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, no effective method has been found so far

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
  • Flight risk behavior identification method based on improved random forest
  • Flight risk behavior identification method based on improved random forest
  • Flight risk behavior identification method based on improved random forest

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0039] The flight risk behavior identification method based on the improved random forest provided by the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0040] Such as figure 1 As shown, the airline flight risk behavior identification method based on improved random forest provided by the invention comprises the following steps carried out in order:

[0041] Step 1) Calibrate the original QAR data and resample to obtain the eigenvectors of the takeoff and landing stages of each flight;

[0042]The complete original QAR data of each flight and each flight recorded by the onboard QAR is taken as an original data set. In order to analyze the flight data of the take-off phase and landing phase accurately, the original QAR data of these two flight phases must be extracted from the complex original QAR data. In addition, since the departure and landing airports of each flight in the original QAR data se...

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 flight risk behavior identification method based on an improved random forest. The method comprises the steps of calibrating and resampling original QAR data and acquiring feature vectors of each sortie flight take-off and landing stage; performing dimension reduction and feature extraction on the feature vector to obtain a final feature vector; constructing a high-riskover-limit event judgment data set in the take-off and landing stages, and improving the high-risk over-limit event judgment data set to obtain an improved high-risk over-limit event judgment data set; building a high-risk over-limit event recognition model based on the improved random forest; and classifying and identifying the data in the improved high-risk over-limit event judgment data set byutilizing an identification model, and making secondary discrimination on unknown risk events. According to the invention, common high-risk over-limit events in take-off and landing stages can be accurately identified; according to the invention, flights with potential flight risks can be screened out for secondary discrimination by safety management personnel, so that pilots can improve technicalactions more timely, and the management personnel can make decisions more leisurely.

Description

technical field [0001] The invention belongs to the technical field of air transport safety big data, and in particular relates to a flight risk behavior identification method based on improved random forest. Background technique [0002] With the continuous expansion of China's civil aviation fleet, China will become the world's largest civil aviation market in the next two decades. However, with the sharp increase in route density, the complexity of airlines' daily operations will increase, and it will also bring greater challenges to flight safety. Although the reliability of aircraft has been greatly improved, and the number of flight accidents caused by mechanical factors has decreased year by year, the number of accidents caused by human factors has remained high, and nearly 90% of the accidents occurred during takeoff and landing. [0003] In order to monitor and manage the flight of the aircraft, domestic passenger planes are equipped with airborne quick access reco...

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 Applications(China)
IPC IPC(8): G06K9/62
CPCG06F18/214G06F18/24323
Inventor 张海刚李俊辰
Owner CIVIL AVIATION UNIV OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com