Study on gas forecast model based on ant colony optimization algorithm

YANG Zhen; LI Xin; FU Hua; WANG Tao

doi:10.13873/j.1000-97872009.10.006

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Study on gas forecast model based on ant colony optimization algorithm

更新时间：2025-09-11

- Study on gas forecast model based on ant colony optimization algorithm
- Vol. 28, Issue 10, Pages: 61-63(2009)
- 作者机构：
  
  辽宁工程技术大学电气与控制工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872009.10.006
  CLC： TD712.5
- Published：2009
- 稿件说明：
移动端阅览
[1]杨桢,李鑫,付华,王涛.基于蚁群优化算法的瓦斯预测模型研究[J].传感器与微系统,2009,28(10):61-63.

YANG Zhen, LI Xin, FU Hua, et al. Study on gas forecast model based on ant colony optimization algorithm[J]. 2009, 28(10): 61-63.
[1]杨桢,李鑫,付华,王涛.基于蚁群优化算法的瓦斯预测模型研究[J].传感器与微系统,2009,28(10):61-63. DOI： 10.13873/j.1000-97872009.10.006.

YANG Zhen, LI Xin, FU Hua, et al. Study on gas forecast model based on ant colony optimization algorithm[J]. 2009, 28(10): 61-63. DOI： 10.13873/j.1000-97872009.10.006.

摘要

针对瓦斯煤尘爆炸和煤与瓦斯突出给煤炭矿山企业带来的危害极大的问题

将蚁群优化算法和BP神经网络技术结合应用到瓦斯涌出量预测

建立比较准确的预测模型。重点研究了BP网络模型的选择与优化训练

通过蚁群算法优化解决了BP神经网络易陷入局部收敛的问题。仿真与实际数据验证表明:改进的神经网络算法对瓦斯涌出量预测能达到良好的效果。

Abstract

In view of the harmful effects of gas and coal dust explosion and gas outburst in coal mine

the ant colony optimization algorithm and BP neural network technology are applied to the prediction of gas emission to establish more accurate prediction models.Focus on the BP network model selection and optimization of training

the ant colony optimization algorithm is used to solve the problem that the BP neural networks is easy to fall into local convergence.Simulation and actual data show that the improved neural network algorithm for the prediction of gas emission can achieve good results.

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references

多传感器模糊信息融合在煤矿安全中的应用 [J]. 付华,高婷,刘洋. 传感器与微系统 . 2008(05)

蚁群优化算法在矿井中的应用 [J]. 华臻,王振翀. 煤炭学报 . 2008(03)

基于蚁群优化算法的模糊神经网络控制器及仿真研究 [J]. 程启明,王勇浩. 上海电力学院学报 . 2006(02)

基于模糊神经网络的信息融合方法在矿井供风系统中的应用 [J]. 付华,孙树生,许振良,冯爱伟,白兰. 煤炭学报 . 2006(02)

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基于混沌时间序列的神经网络对瓦斯涌出量预测 [J]. 黄炜伟,王强,卢爽,刘振江. 煤 . 2005(05)

人工神经网络原理及仿真实例[M]. 机械工业出版社 , 高隽编著, 2003

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