Nonlinear Autoregressive Neural Network and Wavelet Transform for Rainfall Prediction

被引：1

作者：

Benrhmach G. ^{[1
]}

Namir K. ^{[2
]}

Bouyaghroumni J. ^{[1
]}

Namir A. ^{[2
]}

机构：

[1] Laboratory of Analysis, Modelling and Simulation (LAMS), Faculty of Sciences Ben M’sik, Hassan II University, Sidi Othman, Casablanca

[2] Laboratory of Information Technology and Modelling (LITM), Faculty of Sciences Ben M’sik, Hassan II University, Sidi Othman, Casablanca

来源：

Mathematical Models and Computer Simulations | 2022年 / 14卷 / 5期

关键词：

ARIMA-model; ARIMA; artificial neural network; Holt–Winter; rainfall prediction; wavelet decomposition;

D O I：

10.1134/S2070048222050027

中图分类号：

学科分类号：

摘要：

Abstract: Rainfall prediction is one of the most important tools for water management, prompting scientists to develop several techniques in recent years to analyze and predict rainfall. The nature of rainfall data affects the accuracy of the prediction. This paper presents a method for rainfall prediction in two African cities, Meknes located in Morocco and Cape Town in South Africa. The prediction of rainfall in these two cities is presented using a hybrid model, which combines the wavelet decomposition and artificial neural network using two different approaches (WANN-1 and WANN-2). Three other models (ARIMA, Holt–Winter, artificial neural network) were applied to the daily rainfall in the cities of Meknes and Cape Town. The simulation results using MATLAB and R software show that the proposed model is more effective than other used models. © 2022, Pleiades Publishing, Ltd.

引用

页码：837 / 846

页数：9

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