A survey on rainfall forecasting using artificial neural network
by Qi Liu; Yanyun Zou; Xiaodong Liu; Nigel Linge
International Journal of Embedded Systems (IJES), Vol. 11, No. 2, 2019

Abstract: Rainfall has a great impact on agriculture and people's daily travel, so accurate prediction of precipitation is well worth studying for researchers. Traditional methods like numerical weather prediction (NWP) models or statistical models can't provide satisfied effect of rainfall forecasting because of nonlinear and dynamic characteristics of precipitation. However, artificial neural network (ANN) has an ability to obtain complicated nonlinear relationship between variables, which is suitable to predict precipitation. This paper mainly introduces background knowledge of ANN and several algorithms using neural network applied to precipitation prediction in recent years. It is proved that neural network can greatly improve the accuracy and efficiency of prediction.

Online publication date: Wed, 13-Mar-2019

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