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Design of Neural Network models for Daily Rainfall Prediction

by N. A. Charaniya, S. V. Dudul
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 61 - Number 14
Year of Publication: 2013
Authors: N. A. Charaniya, S. V. Dudul
10.5120/9997-4858

N. A. Charaniya, S. V. Dudul . Design of Neural Network models for Daily Rainfall Prediction. International Journal of Computer Applications. 61, 14 ( January 2013), 23-27. DOI=10.5120/9997-4858

@article{ 10.5120/9997-4858,
author = { N. A. Charaniya, S. V. Dudul },
title = { Design of Neural Network models for Daily Rainfall Prediction },
journal = { International Journal of Computer Applications },
issue_date = { January 2013 },
volume = { 61 },
number = { 14 },
month = { January },
year = { 2013 },
issn = { 0975-8887 },
pages = { 23-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume61/number14/9997-4858/ },
doi = { 10.5120/9997-4858 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:09:07.376249+05:30
%A N. A. Charaniya
%A S. V. Dudul
%T Design of Neural Network models for Daily Rainfall Prediction
%J International Journal of Computer Applications
%@ 0975-8887
%V 61
%N 14
%P 23-27
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Rainfall is a random process and prediction of rainfall requires consistent as well as relevant information of meteorological and environmental data. In this paper, two different artificial neural networks models are proposed for consecutive daily rainfall prediction on the basis of the preceding events of rainfall data. Model designed for rainfall forecast is based on the pattern recognition methodology. In this method relevant spatial and temporal feature of rainfall series in past are extracted. These features are then utilized to predict the rainfall in future. Time lag delay neural network has capability to learn from the past event and predict the next value. Rainfall prediction is done on basis of rainfall on previous day to rainfall for the preceding six days. The proposed network is capable of forecasting daily rainfall one day in advance with accuracy of R2 = 0. 96 and NMSE = 0. 0005.

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Index Terms

Computer Science
Information Sciences

Keywords

Artificial neural network Time lag neural network Daily Rainfall Prediction

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