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Study of NH3-N prediction based on nonstationary time series in a sewage River

机译:基于非平稳时间序列的污水河NH 3 -N预测研究

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Using the deterministic analysis of non-stationary time series, this paper focuses on the prediction of NH3-N in a sewage River. Considering environmental hazards of indiscriminate discharge of sewage, the experiment was performed on a sewage river of selected area. NH3-N was measured at selected seven sampling locations from Aug 2007 to Aug. 2008. We conducted a total of nine samples. During the experiment, the sampling time is basically the same and time intervals of sampling are also consistent, therefore the sampled data (seven samples) can be looked on as a sequence of time. According to the requirements of time series analysis, manipulate the data and test the stationarity of the series. By time series analysis, an exponential smoothing of NH3-N is developed. As long as we know the actual value and predicted value of NH3-N concentration in last period, we can predict the next NH3-N concentration. Significant test of model parameters and adaptive testing of the model show that the exponential smoothing of NH3-N was significant. Using the data from water quality testing department of the city to test the model, which indicates that the veracity of the model was 82.9%, which meets the precision requirement of the mode1.
机译:通过对非平稳时间序列的确定性分析,重点研究了污水河中NH 3 -N的预测。考虑到随意排放污水的环境危害,在选定地区的污水河上进行了试验。从2007年8月至2008年8月,在选定的七个采样点测量了NH 3 -N。我们总共进行了9个采样。在实验过程中,采样时间基本相同,采样时间间隔也一致,因此可以将采样数据(七个采样)看成是一个时间序列。根据时间序列分析的要求,处理数据并测试序列的平稳性。通过时间序列分析,开发了NH 3 -N的指数平滑算法。只要知道上一个时期NH 3 -N的实际值和预测值,就可以预测下一个NH 3 -N的浓度。模型参数的显着检验和模型的自适应检验表明,NH 3 -N的指数平滑性很显着。利用市水质检测部门的数据对模型进行检验,表明模型的准确性为82.9%,符合模型1的精度要求。

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