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

Big data-based method and system for predicting variable sliding time

A technology of sliding time and big data, applied in the field of civil aviation information, it can solve the problems of different results and efficiency, and labor efficiency cannot ensure efficiency.

Pending Publication Date: 2019-10-22
四川青霄信息科技有限公司
View PDF2 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

There are the following problems in manual operation: first, the different experience and familiarity of different personnel will lead to wildly different results and efficiency; second, certain errors are inevitable due to subjective and objective factors; third, manual efficiency cannot ensure efficiency when dealing with a large number of concurrent data

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
  • Big data-based method and system for predicting variable sliding time
  • Big data-based method and system for predicting variable sliding time
  • Big data-based method and system for predicting variable sliding time

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0062] In order to make the technical means, creative features, goals and effects achieved by the present invention easy to understand, the present invention will be further described below in conjunction with specific embodiments.

[0063] As an embodiment, the present invention proposes a method for predicting variable sliding time based on big data, comprising the following steps:

[0064] Analyze the historical data in the airport collaborative decision-making system database, extract flight departure operation data from it, determine the main influencing parameters of flight departure, set the weight value of each main influencing parameter, and dynamically adjust each main influencing parameter weight ratio;

[0065] Import the historical data that mainly affects the parameters for parameter learning, import the data of the main parameters recently obtained for incremental learning, use the gradient boosting tree model for modeling, and fit a basis function , to obtain...

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 big data-based method and system for predicting the variable sliding time and relates to the field of civil aviation information. The method comprises the following steps: analyzing historical data in an airport collaborative decision-making system database, extracting flight departure operation data from the historical data, determining main influence parameters of flight departure, setting a weight value and dynamically adjusting a weight proportion; modeling by adopting a gradient boosting tree model to obtain a variable sliding time dynamic estimation model, inputting actual data of main influence parameters into the variable sliding time dynamic estimation model, estimating probability distribution of variable sliding time, and calculating an expected value;performing visual display on the variable sliding time. According to the method, the variable sliding time is intelligently predicted through manual prediction based on the constructed A-CDM system. The large-area flight delay is prevented and relieved through big data visualization auxiliary decision making.

Description

technical field [0001] The invention relates to the field of civil aviation information, in particular to a method and system for predicting variable sliding time based on big data. Background technique [0002] China's civil aviation industry is developing rapidly, but the current level of informatization construction in the civil aviation industry is relatively lagging behind: in terms of hardware, especially the level of network construction lags behind business development, there are problems such as incomplete coverage and limited transmission speed; in terms of software, there are A large number of redundant construction, data islands, lack of data interconnection, and the system urgently needs to be upgraded. In the face of challenges, the civil aviation industry hopes to make full use of modern information technology to provide passenger and cargo transportation guarantee and digital management, visual presentation, and intelligent support for civil aviation airpor...

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): G06Q10/04G06Q10/06G06Q50/30
CPCG06Q10/04G06Q10/06316G06Q50/40
Inventor 闵钰麟胡兴建
Owner 四川青霄信息科技有限公司
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