Monthly Rainfall Prediction Using Wavelet Neural Network Analysis

被引：161

作者：

Ramana, R. Venkata ^{[1
]}

Krishna, B. ^{[2
]}

Kumar, S. R. ^{[1
]}

Pandey, N. G. ^{[1
]}

机构：

[1] Natl Inst Hydrol, Ctr Flood Management Studies, Patna 801505, Bihar, India

[2] Natl Inst Hydrol, Delta Reg Ctr, Kakinada 533003, Andhra Pradesh, India

来源：

WATER RESOURCES MANAGEMENT | 2013年 / 27卷 / 10期

关键词：

Rainfall; Training Decomposition; Neural network and wavelet; MODEL; DECOMPOSITION; TRANSFORM;

D O I：

10.1007/s11269-013-0374-4

中图分类号：

TU [建筑科学];

学科分类号：

0813 ;

摘要：

Rainfall is one of the most significant parameters in a hydrological model. Several models have been developed to analyze and predict the rainfall forecast. In recent years, wavelet techniques have been widely applied to various water resources research because of their time-frequency representation. In this paper an attempt has been made to find an alternative method for rainfall prediction by combining the wavelet technique with Artificial Neural Network (ANN). The wavelet and ANN models have been applied to monthly rainfall data of Darjeeling rain gauge station. The calibration and validation performance of the models is evaluated with appropriate statistical methods. The results of monthly rainfall series modeling indicate that the performances of wavelet neural network models are more effective than the ANN models.

引用

页码：3697 / 3711

页数：15

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