基于三种时间序列模型的矿井涌水量预测  

Prediction of mine water inflow based on three time series models

作　　者：刘晓丹 潘国营[1] LIU Xiaodan;PAN Guoying(School of Resources&Environment,Henan Polytechnic University,Jiaozuo 454000,China)

机构地区：[1]河南理工大学资源环境学院,河南焦作454000

出　　处：《矿业安全与环保》2022年第2期91-95,101,共6页Mining Safety & Environmental Protection

摘　　要：为实现矿井涌水量的有效预测,提高预测精度,基于鹤壁八矿2009—2019年的月度涌水量数据,运用时间序列分析软件Eviews9.0建立了X12季节调整、ARIMA(2,0,1)、SARIMA(2,0,1)×(0,1,1)_(12)模型,并使用2019年月度涌水量数据进行验证。通过比较3种模型的预测误差,探讨鹤壁八矿矿井涌水量预测的最优模型。结果显示,3种模型对涌水量的预测效果都比较好,其中预测精度最高的模型为ARIMA(2,0,1),SARIMA(2,0,1)×(0,1,1)_(12)模型次之,X12季节调整模型略差。对3种模型的可能误差来源进行了研究分析,可为矿井涌水量预测提供新思路。In order to realize the effective prediction of mine water inflow and improve the prediction accuracy,based on the monthly water inflow data of Hebi No.8 Mine from 2009 to 2019,this paper uses the time series analysis software Eviews9.0 to establish three models.They are the X12 seasonal adjust model,ARIMA(2,0,1)model and SARIMA(2,0,1)×(0,1,1)_(12) model,the monthly water inflow in 2019 is used for verification.By comparing the prediction errors of the three models,the optimal model for predicting mine water inflow in Hebi No.8 Mine is discussed.The results show that the three models have good prediction effects on water inflow,among which ARIMA(2,0,1)has the highest prediction accuracy,followed by SARIMA(2,0,1)×(0,1,1)_(12) model,and X12 seasonal adjust model is slightly inferior.The possible error sources of the three models are studied and analyzed,which can provide a new idea for the prediction of mine water inflow.

关 键 词：矿井涌水量 X12季节调整模型 ARIMA模型 SARIMA模型 评价指标 

分 类 号：TD742[矿业工程—矿井通风与安全]