基于指数平滑模型的矿区重金属污染时间序列预测

Yunzhang Rao, Shuitai Xu, Lingyan Xiong
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引用次数: 1

摘要

矿区重金属污染具有时间序列特征,可以用指数平滑模型进行预测。根据某铜矿排污口下游500m地表水监测点1995-2007年的铜(Cu)监测数据,采用三次指数平滑法,通过选择不同的平滑系数a,建立了重金属Cu的预测模型。将该预测模型应用于2005 - 2007年对排污口下游500m废水中Cu含量的预测。结果表明,预测结果与相应的实际监测值比较误差小于5%,满足了试验要求。预测结果表明,矿区今后仍将处于铜污染状态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Time series prediction of heavy metal contamination in mining areas based on exponential smoothing model
Heavy metal contamination in mining areas has the features of time series, so it can be predicted with exponential smoothing model. On the basis of 1995–2007 monitoring data of Copper (Cu) at the surface water monitoring point 500m to the downstream of the sewage outlet in a copper ore, with cubic exponential smoothing method, the predicting model of heavy metal Cu is established through selecting different smoothing coefficient a. After applying the predicting model to predicting the content of Cu in the wastewater 500m to the sewage outlet from 2005 to 2007, it is found that the error of comparing the predicted result with correspondent actual monitoring values is less than 5%, which satisfies the requirements after testing. The predicting result shows that the mining area will be still in the contamination of Cu in the future.
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