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Application of Self-Adaptive Exponential Smoothing Method in the Water Quality Forecast of Poyang Lake

机译:自适应指数平滑方法在鄱阳湖水质预测中的应用

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The smoothing parameter is a constant when forecasting water quality using exponential smoothing, which usually renders the error to be enlarged, but the assumption of constant is out of accord with the practice. Based on the deep analysis of deficiency of traditional exponential smoothing, this paper establishes self-adaptive exponential smoothing model and compares the forecast result. It is proved that the dynamic characteristic of water quality can be better reflected and the forecasting precision can be improved further by self-adaptive exponential smoothing model.
机译:使用指数平滑预测水质时,平滑参数是一种常数,这通常会使误差放大,但常量的假设与练习不符。基于对传统指数平滑缺陷的深度分析,本文建立了自适应指数平滑模型,并比较了预测结果。事实证明,可以更好地反映水质的动态特性,并且通过自适应指数平滑模型可以进一步提高预测精度。

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