摘要
为有效、准确地预测回采工作面绝对瓦斯涌出量,基于变分模态分解(VMD)方法;差分进化(DE)算法和相关向量机(RVM)原理,提出回采工作面绝对瓦斯涌出量的VMD—DE-RVM区间预测方法;通过VMD方法将绝对瓦斯涌出量分解为若干固有模态分量并分析其局部特征,分别建立每个固有模态分量的RVM预测模型,并通过DE算法优化模型参数以提高预测精度;加权叠加各个分量的预测结果得到绝对瓦斯涌出量预测结果,并将其与经验模态分解方法所得结果对比。结果表明:应用该方法预测回采工作面瓦斯涌出量,能弱化瓦斯涌出量的局部特征,得到置信度为95%时涌出量预测区间有效度为100%,平均绝对误差为0.096m^3/min,平均相对误差为2.43%,预测精度有所提高。
In order to effectively and accurately predict the absolute gas emission of the mining face,a VMD-DE-RVM interval prediction method was worked out for absolute gas emission from a mining face based on VMD method,DE algorithm and RVM principle.For working out the method,the absolute gas emission was decomposed into several intrinsic mode components by VMD method and the local characteristics were analyzed.RVM prediction models were built for the intrinsic mode component,and the model parameters were optimized by DE algorithm to improve the prediction accuracy.Prediction results of the components were weighted and superimposed to obtain an absolute gas emission prediction result.A prediction result comparison was made between the three models.The results show that the method worked out by the authors can weaken the local characteristics of gas emission,and the prediction interval effectiveness is 100%,the average absolute error is 0.096m3/min and the average relative error is 2.43% when the confidence is 95%,and the prediction accuracy is improved.
作者
代巍
付华
冀常鹏
王英杰
DAI Wei;FU Hua;JI Changpeng;WANG Yingjie(School of Safety Science and Engineering,Liaoning Technical University,Fuxin Liaoning 123000,China;School of Electrical and Control Engineering,Liaoning Technical University,Huludao Liaoning 125105,China;School of Electronic and Information Engineering,Liaoning Technical University,Huludao Liaoning 125105,China;Liaoning Open-pit Mining Equipment Engineering Technology Research Center,Fuxin Liaoning 123000;Liaoning Hans Mining Group Co.,Ltd,Fuxin Liaoning 123000)
出处
《中国安全科学学报》
CAS
CSCD
北大核心
2018年第9期109-115,共7页
China Safety Science Journal
基金
国家自然科学基金资助(51274118)
