Method and device for predicting airport traffic congestion based on long short-term memory (LSTM) model

A technology for traffic congestion and airports, applied in the fields of computer science and intelligent transportation, it can solve problems that need to be improved, and achieve the effect of improving accuracy

Inactive Publication Date: 2018-11-27
CAPITAL UNIV OF ECONOMICS & BUSINESS +1
View PDF12 Cites 29 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

These methods have achieved good application results in their specific scenarios, but still need to be improved

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
  • Method and device for predicting airport traffic congestion based on long short-term memory (LSTM) model
  • Method and device for predicting airport traffic congestion based on long short-term memory (LSTM) model
  • Method and device for predicting airport traffic congestion based on long short-term memory (LSTM) model

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0062] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided for more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0063] refer to figure 1 As shown, the airport traffic congestion prediction method based on the LSTM model provided by the embodiment of the present invention includes: S101~S103;

[0064] S101. Real-time acquisition of traffic condition information of roads within a preset range around the airport, airport flight take-off and landing information, and aviation weather information within a preset range around the airport;

[0065]...

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 relates to a method and a device for predicting airport traffic congestion based on a long short-term memory (LSTM) model. The method comprises the steps of acquiring traffic condition information and airport flight takeoff and landing information of a road within a preset range around an airport as well as aviation meteorological information within a preset range around the airport;inputting the traffic condition information, the flight takeoff and landing information and the aviation meteorological information into the LSTM model; acquiring an output result of the LSTM model,wherein the output result is a predicted congestion index of the road within the preset range around the airport in a future time period. The method is based on the consideration of space and time effects, and the aviation meteorological information is added; intra-regional traffic is regarded as a space-time related system; the prediction result is obtained based on the LSTM model, so that the accuracy of the road congestion index prediction within the preset range around the airport is further improved.

Description

technical field [0001] The invention relates to the fields of computer science and intelligent transportation technology, in particular to a method and device for predicting airport traffic congestion based on an LSTM model. Background technique [0002] With the rapid advancement of my country's urbanization process, urban congestion has become one of the important factors that plague urban development. How to improve the efficiency of urban traffic operations and alleviate the pressure of congestion has become a problem that must be solved for cities to achieve sustainable and healthy development. In the face of challenges, major cities and navigation companies have released "traffic congestion delay index" as an important means of traffic management and guidance. For example, the "Traffic Index" and "Traffic Operation Analysis Report" issued by the Beijing Municipal Commission of Transportation, and the "Congestion Ranking of China's Major Cities" released by AutoNavi. ...

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): G08G1/01G08G5/00G06Q10/04G06Q50/26
CPCG06Q10/04G06Q50/26G08G1/0137G08G5/00
Inventor 周芳张波李强缪明月张军李国军
Owner CAPITAL UNIV OF ECONOMICS & BUSINESS
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

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap