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Cite this article:林祥志.小波ANFIS模型预测分析诸暨站降雨量[J].灌溉排水学报,,():-.
linxiangzhi.小波ANFIS模型预测分析诸暨站降雨量[J].灌溉排水学报,,():-.
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DOI:
Forecast and Analysis of Rainfall at Zhuji Station by Wavelet ANFIS Model
linxiangzhi
Zhejiang Water Conservancy and Hydropower Project Quality and Safety Supervision and Management Center
Abstract:
诸暨站是浦阳江流域一个重要的雨量站。通过对诸暨站降水量的预测,可以为浦阳江流域防洪决策提供依据。目前有许多预测方法,如人工神经网络等,但这些方法不是很精确。本文利用小波分解降雨序列,然后利用ANFIS建模分解,再结合这些系列,表明预测精度提高了很多,适合于降雨预报。 Zhuji Rainfall Station is an important rainfall station in Puyang River Basin. The prediction of precipitation at Zhuji Station can provide a basis for flood control decision-making in Puyang River Basin. At present, there are many prediction methods, such as artificial neural network, but these methods are not very accurate. In this paper, we use wavelet to decompose rainfall series, then use ANFIS to model and decompose, and combine these series, which shows that the prediction accuracy has been improved a lot, and it is suitable for rainfall prediction.
Key words:  Wavelet; ANFIS model; Forecast; Rainfall