Coal-body gas permeability predicting method based on LVQ-CPSO-BP algorithm

A technology of LVQ-CPSO-BP and prediction method, applied in the field of coal gas permeability prediction based on LVQ-CPSO-BP algorithm

Inactive Publication Date: 2017-06-20
XINJIANG UNIVERSITY
View PDF6 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the single prediction model algorithm based on BP neural network can only answer specific questions. Therefore, the research on the hybrid prediction model based on the combination algorithm has been developed rapidly. The intelligent optimization algorithm combined with the neural network analyzes the change characteristics of t

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
  • Coal-body gas permeability predicting method based on LVQ-CPSO-BP algorithm
  • Coal-body gas permeability predicting method based on LVQ-CPSO-BP algorithm
  • Coal-body gas permeability predicting method based on LVQ-CPSO-BP algorithm

Examples

Experimental program
Comparison scheme
Effect test

experiment example

[0066] Such as figure 1 as shown,

[0067] The coal gas permeability prediction method based on the LVQ-CPSO-BP algorithm consists of the following steps:

[0068] Screening of main influencing factors and determination of delamination critical value and stress inflection point

[0069] The coal gas permeability is closely related to the geological time and space characteristics. With the change of the coal mining process, it presents the characteristics of time-varying, nonlinear, fuzzy, etc., and shows the characteristics of dynamic changes. The influencing factors are mainly reflected in the geological structure, geological coal seam structure, coal seam mining depth, coal quality characteristics, etc. macroscopically, and mainly reflected in the effective stress, temperature, gas pressure, compressive strength, pore structure, etc. at the microscopic level. The above factors are ignored. The relationship between permeability and permeability cannot truly reflect the inte...

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

A learning vector quantization (LVQ)-chaos particle swarm optimization (CPSO)-back propagation(BP) coal-body gas permeability predicting method is provided based on an algorithm of LVQ neural network classifying, the CPSO and BP neural network predicting. A critical value is determined, and the buried depth of a coal seam is divided into two layers. Based on the inflection point relation existing between effective stress and gas permeability, an inflection point value is determined, and the effective stress is divided into two sections. Four microcosmic sample parameters are classified and identified through the LVQ according to the inflection point characteristic, a BP neural network is adopted to study and train, and the predicting result is output, and a weight value and a threshold of the BP neural network are optimized through the CPSO. Finally, the predicting result of the built LVQ-CPSO-BP algorithm is verified, and the predicting results of a BP algorithm, a GA-BP algorithm and a PSO-BP algorithm are compared and analyzed.

Description

technical field [0001] The invention relates to the field of coal gas permeability prediction, in particular to a coal gas permeability prediction method based on the LVQ-CPSO-BP algorithm. Background technique [0002] Coal mine gas disaster is one of the main disasters in the process of coal mining. Affected by geological conditions, mine gas mostly seeps and moves in an unstable state in the coal seam. Since the gas permeability is closely related to the earth's time and space characteristics such as in-situ stress, temperature, and gas pressure, the gas permeability presents time-varying, nonlinear, and fuzzy characteristics. How to accurately predict the dynamic change of coal gas permeability , which is of great significance to prevent the occurrence of coal mine gas disasters in mining. [0003] Researchers at home and abroad have studied the changes in coal gas permeability. Lu Runsheng et al. studied the differences in coal gas permeability under different structur...

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): E21F7/00G06F17/50G06N3/08
CPCE21F7/00G06F30/20G06N3/084
Inventor 谢丽蓉路朋王晋瑞高磊牛永朝王忠强
Owner XINJIANG UNIVERSITY
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