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

Prediction method of general aircraft aviation material demand based on mpso-bp network

A technology of MPSO-BP and demand forecasting, applied in neural learning methods, biological neural network models, etc.

Inactive Publication Date: 2018-07-27
SHENYANG AEROSPACE UNIVERSITY
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] In order to solve the problem of forecasting demand for general aircraft aviation materials, the present invention proposes a method for forecasting general aircraft aviation material demand based on MPSO-BP network

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
  • Prediction method of general aircraft aviation material demand based on mpso-bp network
  • Prediction method of general aircraft aviation material demand based on mpso-bp network
  • Prediction method of general aircraft aviation material demand based on mpso-bp network

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0057] see Figure 1-Figure 6 And Table 1-Table 2, the general aircraft material demand forecasting method based on MPSO-BP network, this method analyzes and studies the main influencing factors of general aircraft material demand, adopts two strategies of adaptive variation and setting linear decreasing inertia weight The defects of the basic PSO algorithm are improved, and the prediction model of the improved particle swarm algorithm to optimize the BP network is constructed.

[0058] Step 1: Analysis of factors affecting the demand for general aircraft materials.

[0059] (1) Calculate the flight time (P 1 )

[0060] (2) Aviation material failure rate (P 2 )

[0061] (3) Average time between failures of aviation materials (P 3 )

[0062] (4) Technical level of maintenance personnel (P 4 )

[0063] (5) Environmental factors (P 5 )

[0064] Step 2: Improvements to the basic PSO algorithm.

[0065] The PSO algorithm randomly initializes a group of particles, and the...

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 brings forward a general airplane air-material demand prediction method based on an MPSO-BP network with the combination of a particle swarm algorithm and a BP network. The method includes: firstly, analysis and research of main influence factors of the general airplane air-material demand are conducted, then the basic principle of the BP network, the PSO algorithm, and the improved strategy of the PSO algorithm are introduced, and a prediction model for improving the particle swarm algorithm and optimizing the BP network is built. Five main influence factors of the general airplane air-material demand are regarded as the input of the network, the demand quantity of the general airplane air-material is regarded as the output, and a nonlinear mapping relation between the input and the output is established. According to the method, accurate prediction of the general airplane air-material demand quantity can be realized, the non-linear fitting capability and generalization capability are very good, the convergence efficiency is improved, the possibility of falling to a local minimum value is reduced, the prediction precision is higher, and the application effect in the general airplane air-material demand prediction is good.

Description

technical field [0001] The invention belongs to the field of general aircraft aviation material management, and in particular relates to a method for forecasting general aircraft aviation material demand based on an intelligent algorithm to optimize a BP network. Background technique [0002] General aircraft material demand forecasting directly affects the material guarantee and cost management of general aviation enterprises. Inaccurate forecasting will cause material shortage or waste, while accurate forecasting can greatly reduce costs while meeting high guarantee rates. Therefore, how to scientifically Determining the demand for general aircraft materials has always been a key research topic for general aviation companies. [0003] At present, some research results have been obtained in the research on the forecasting method of aviation material demand. Jia Zhiyu researched the forecast method of aviation material consumption based on the summation autoregressive movin...

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): G06N3/08
CPCG06N3/08
Inventor 陈侠王拓
Owner SHENYANG AEROSPACE UNIVERSITY
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