文章基本信息

标题：Hybrid Wavelet-Postfix-GP Model for Rainfall Prediction of Anand Region of India
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作者：Vipul K. Dabhi ; Sanjay Chaudhary
期刊名称：Advances in Artificial Intelligence
印刷版ISSN：1687-7470
电子版ISSN：1687-7489
出版年度：2014
卷号：2014
DOI：10.1155/2014/717803
出版社：Hindawi Publishing Corporation
摘要：An accurate prediction of rainfall is crucial for national economy and management of water resources. The variability of rainfall in both time and space makes the rainfall prediction a challenging task. The present work investigates the applicability of a hybrid wavelet-postfix-GP model for daily rainfall prediction of Anand region using meteorological variables. The wavelet analysis is used as a data preprocessing technique to remove the stochastic (noise) component from the original time series of each meteorological variable. The Postfix-GP, a GP variant, and ANN are then employed to develop models for rainfall using newly generated subseries of meteorological variables. The developed models are then used for rainfall prediction. The out-of-sample prediction performance of Postfix-GP and ANN models is compared using statistical measures. The results are comparable and suggest that Postfix-GP could be explored as an alternative tool for rainfall prediction.