摘要
为解决烟(粉)尘排放量预测模型中原始数据存在干扰因素且不稳定的问题,提出了一种结合弱化缓冲算子优化的灰色FGM预测模型,对废气中烟(粉)尘排放量的变化进行预测和拟合。相对于单一的灰色FGM预测模型,优化的预测模型引入了弱化缓冲算子。基于2012—2017年全国废气中烟(粉)尘的年排放量数据,运用3种弱化缓冲算子对原始序列进行处理,对比GAWBO和AWBO以及WAWBO 3种弱化缓冲算子处理后得到的预测结果,并用原始数据对预测结果进行检验分析,结果表明运用WAWBO算法优化的FGM模型预测的数据精度最高,相对误差只有2.767%,预测结果与实际烟(粉)尘排放情况更符。研究表明,使用弱化算子优化的FGM模型拟合程度更高,且具有较高的预测精度,扩宽了该预测模型的应用范围。
The purpose of this paper is to introduce an improved prediction model for predicting smoke(dust)emissions from exhaust gases and optimize the traditional fractional-order cumulative gray prediction(FGM(1,1))by weakening the buffer operator.Besides,the optimization model solves the problem of low reliability of prediction results due to the volatility of the original data.The smoke(dust)emissions in exhaust gases from 2012 to 2017 are selected and the statistical data are analyzed and studied.It is found that the smoke(dust)emissions led to non-linear fluctuations in the statistical data due to the interference of various uncertainties.In the paper,the fractional-order cumulative gray prediction model(FGM(1,1))optimized by the weak buffer operator is used to predict the amount of smoke(dust)in exhaust gases from 2012 to 2017,and the original series is processed by three weak buffer operators.The optimal order of the fractional-order cumulative gray prediction model(FGM(1,1))calculated by MATLAB software using the particle swarm optimization algorithm is 0.7.The prediction results obtained after comparing the three weak buffer operators of GAWBO,AWBO and WAWBO,and the original data are used to test and analyze the prediction results.The results show that the prediction accuracy of the fractional-order cumulative gray prediction model(FGM(1,1))optimized by the weak buffer operator is significantly higher than that of the traditional fractional-order cumulative gray prediction model(FGM(1,1)),and the prediction accuracy of the fractional-order cumulative gray prediction model(FGM(1,1))optimized by WAWBO is the highest,with the absolute value of the relative error only 2.767%,with a small value of prediction error,correcting the volatility problem of sudden increase in smoke(dust)emissions that occurred in FY2014 and FY2015.The fractional-order cumulative gray prediction model(FGM(1,1))optimized by WAWBO predicts the smoke(dust)emissions in exhaust gases from 2018 to 2022,and the prediction results are 7.199,6.397,5.
作者
刘杰
傅钰
马倩
张悦
邓禾苗
LIU Jie;FU Yu;MA Qian;ZHANG Yue;DENG He-miao(Faculty of Public Security and Emergency Management,Kunming University of Science and Technology,Kunming 650093,China)
出处
《安全与环境学报》
CAS
CSCD
北大核心
2022年第2期941-946,共6页
Journal of Safety and Environment
基金
云南省重点研发计划项目(202003AC100002)
云南省教育厅科学研究基金项目(2018JS034)。
关键词
环境工程学
烟粉尘排放量
弱化缓冲算子
灰色预测模型
environmental engineering
smoke(dust)emissions
weakening buffer operator
grey forecasting model
