章万静,郑先彬,赵陇,韩锐

• 1:江苏省电子产品装备制造工程技术研发中心

摘要(Abstract)：

将矿井瓦斯作为研究对象,结合小波神经网络构建预测模型,并采用改进算法对预测模型进行训练和进化。优化网络中的模型参数,完成对瓦斯浓度的短时预测,为瓦斯监控及提前预警提供客观的参考和依据。通过对预测模型的432次训练进化和Matlab仿真表明,该模型预测精度高,训练误差小,收敛速度快,能够满足实际工程应用的要求。

关键词(KeyWords)： 小波神经网络;算法改进;瓦斯预测;短时预测;预测模型;Matlab

Abstract:

Keywords:

基金项目(Foundation): 国家重点星火计划项目(2011GA690005);; 江苏省现代服务业发展专项引导资金项目(KA122117019)~~

作者(Author): 章万静,郑先彬,赵陇,韩锐

DOI: 10.16652/j.issn.1004-373x.2018.23.013

参考文献(References)：

• [1]李圣普,王小辉.基于IPSO-SVM的瓦斯突出危险程度预测[J].现代电子技术,2016,39(4):21-25.LI Shengpu,WANG Xiaohui.Gas outburst risk prediction based on IPSO-SVM[J].Modern electronics technique,2016,39(4):21-25.
• [2]宿敬肖,王政,杨静宜,等.优化神经网络模型在瓦斯涌出预测中的应用[J].煤矿安全,2017,48(5):140-143.SU Jingxiao,WANG Zheng,YANG Jingyi,et al.Application of neural network model optimization in predicting gas emission[J].Safety in coal mines,2017,48(5):140-143.
• [3]李杰,康天合,康官先.基于IGSA-ELM模型的回采工作面瓦斯涌出量预测[J].煤矿安全,2016,47(1):155-158.LI Jie,KANG Tianhe,KANG Guanxian.Gas emission quantity prediction of working face based on IGSA-ELM model[J].Safety in coal mines,2016,47(1):155-158.
• [4]钱建生,邱春荣,李紫阳,等.深度学习耦合粒子群优化SVM的瓦斯浓度预测[J].煤矿安全,2016,47(11):173-176.QIAN Jiansheng,QIU Chunrong,LI Ziyang,et al.Gas emission quantity prediction based on particle swarm optimization of SVM and deep learning network[J].Safety in coal mines,2016,47(11):173-176.
• [5]沈仲辉,李希建.基于改进的最小二乘法瓦斯涌出量预测[J].工业安全与环保,2017,43(1):88-90.SHEN Zhonghui,LI Xijian.Gas extraction prediction based on the improved least square method[J].Industrial safety and environmental protection,2017,43(1):88-90.
• [6]史峰,王小川,郁磊,等.Matlab神经网络30个案列分析[M].北京:北京航空航天大学出版社,2010:208-217.SHI Feng,WANG Xiaochuan,YU Lei,et al.30 cases analysis of Matlab neural network[M].Beijing:BUAA Press,2010:208-217.
• [7]王雅琳,黄凯华,黄天红,等.基于改进小波神经网络的极谱法多金属离子浓度检测信号的在线解析[J].中南大学学报(自然科学版),2016,47(1):100-107.WANG Yalin,HUANG Kaihua,HUANG Tianhong,et al.Online analysis on polarographic detection signal of multi-metal ion concentrations based on improved wavelet neural networks[J].Journal of Central South University(science and technology),2016,47(1):100-107.
• [8]张德丰.Matlab神经网络应用设计[M].北京:机械工业出版社,2009:266-270.ZHANG Defeng.Applied design of Matlab neural network[M].Beijing:China Machine Press,2009:266-270.
• [9]葛玉辉,熊永良,陈志胜,等.基于小波神经网络的GPS可降水量预测研究[J].测绘科学,2015,40(9):28-32.GE Yuhui,XIONG Yongliang,CHEN Zhisheng,et al.Prediction method of GPS precipitation based on wavelet neural network[J].Science of surveying and mapping,2015,40(9):28-32.
• [10]付华,刘汀,张胜强,等.基于改进ABC-GRNN模型的煤矿瓦斯浓度预测研究[J].控制工程,2017,24(4):881-887.FU Hua,LIU Ting,ZHANG Shengqiang,et al.Gas concentration prediction model of coal mine based on improved ABC-GRNN algorithm[J].Control engineering of China,2017,24(4):881-887.
• [11]赵鑫,宋广军,李诚.改进BP神经网络的煤与瓦斯突出预测[J].计算机仿真,2012,29(6):195-198.ZHAO Xin,SONG Guangjun,LI Cheng.Dangerous forecast of coal and gas bursting based on improved back propagation neural network[J].Computer simulation,2012,29(6):195-198.
• [12]罗云芳.一种BP网络校正算法的实验室智能温控系统研究[J].现代电子技术,2015,38(20):84-87.LUO Yunfang.Research on laboratory?s intelligent temperature control system based on BP network correction algorithm[J].Modern electronics technique,2015,38(20):84-87.