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基于APSO-WLS-SVM的含瓦斯煤渗透率预测模型

毛志勇 黄春娟 路世昌 韩榕月

毛志勇, 黄春娟, 路世昌, 韩榕月. 基于APSO-WLS-SVM的含瓦斯煤渗透率预测模型[J]. 煤田地质与勘探, 2019, 47(2): 66-71,78. doi: 10.3969/j.issn.1001-1986.2019.02.011
引用本文: 毛志勇, 黄春娟, 路世昌, 韩榕月. 基于APSO-WLS-SVM的含瓦斯煤渗透率预测模型[J]. 煤田地质与勘探, 2019, 47(2): 66-71,78. doi: 10.3969/j.issn.1001-1986.2019.02.011
MAO Zhiyong, HUANG Chunjuan, LU Shichang, HAN Rongyue. Model of gas-bearing coal permeability prediction based on APSO-WLS-SVM[J]. COAL GEOLOGY & EXPLORATION, 2019, 47(2): 66-71,78. doi: 10.3969/j.issn.1001-1986.2019.02.011
Citation: MAO Zhiyong, HUANG Chunjuan, LU Shichang, HAN Rongyue. Model of gas-bearing coal permeability prediction based on APSO-WLS-SVM[J]. COAL GEOLOGY & EXPLORATION, 2019, 47(2): 66-71,78. doi: 10.3969/j.issn.1001-1986.2019.02.011

基于APSO-WLS-SVM的含瓦斯煤渗透率预测模型

doi: 10.3969/j.issn.1001-1986.2019.02.011
基金项目: 

国家自然科学基金项目(70971059)

详细信息
    第一作者:

    毛志勇,1976年生,男,陕西汉中人,博士,副教授,硕士生导师,从事数据挖掘、信息系统、系统工程等方面研究工作.E-mail:405949570@qq.com

  • 中图分类号: TD712;P618.11

Model of gas-bearing coal permeability prediction based on APSO-WLS-SVM

Funds: 

National Natural Science Foundation of China(70971059)

  • 摘要: 为了较准确预测含瓦斯煤渗透率,有效预防瓦斯安全事故,提出自适应粒子群算法(APSO)优化的加权最小二乘法支持向量机(WLS-SVM)算法。根据对含瓦斯煤渗透率的相关理论及文献研究分析,选取有效应力、瓦斯压力、温度和抗压强度作为主要特征指标,采用APSO算法对WLS-SVM模型的组合参数(C、σ)寻优,建立APSO-WLS-SVM含瓦斯煤渗透率预测模型。结合现场实测资料中的40组数据作为训练样本,其余10组为预测样本,对该模型进行训练与检验,并将其预测结果与利用PSO-WLS-SVM和WLS-SVM模型的预测结果进行对比。结果表明:APSO-WLS-SVM模型的预测效果优于另外2个模型,提高了煤体渗透率的预测性能与泛化能力。

     

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出版历程
  • 收稿日期:  2018-04-04
  • 发布日期:  2019-04-25

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