基于ARIMA模型的湘江流域DO和NH_4^+-N含量贝叶斯预测  

Prediction the contents of DO and NH_4^+-N in Xiangjiang river basin using Bayesian approach based on the ARIMA model

作　　者：刘潭秋[1] 王巧玲[2] 

机构地区：[1]长沙理工大学经济与管理学院,湖南长沙410114 [2]长沙环境保护职业技术学院,湖南长沙410004

出　　处：《湖南农业大学学报（自然科学版）》2017年第5期575-580,共6页Journal of Hunan Agricultural University(Natural Sciences)

基　　金：全国统计科学研究计划项目(2013LY027)

摘　　要：为实时把控湘江流域水质的变化趋势,采用污染比较严重的湘江流域长沙段和益阳段水质指标溶解氧(DO)和氨氮(NH_4^+-N)含量的监测数据,用贝叶斯方法推断经典的ARIMA时间序列模型,并用马尔可夫链蒙特卡罗(MCMC)模拟方法对DO和NH_4^+-N含量进行贝叶斯预测。结果表明,该模型的贝叶斯预测能实现对湘江流域长沙段和益阳段水质指标DO和NH_4^+-N含量的精确点预测、区间预测和概率预测。To master the variation of water quality in case of water security event and to take measures in advance against that in Xiangjiang river basin, the monitoring data of DO and NH_4~＋-N in Changsha section and Yiyang section, which are two serious pollution river sections in the basin, were adopted for predicting their contents through ARIMA model which infers a classical time series model using Bayesian approach, the model parameters and prediction results were simulated by employing Markov Chain Monte Carlo（MCMC） method. The results showed that Bayesian approach in the model could accurately predict contents of DO and NH_4~＋-N at section level, interval level, and probability level in the two selected sections.

关 键 词：湘江流域 溶解氧(DO) 氨氮(NH4+-N)含量 贝叶斯预测 马尔可夫链蒙特卡罗(MCMC)模拟方法 

分 类 号：S273.2[农业科学—农业水土工程] X52[农业科学—农业工程]