Artificial Neural Network for Monthly Rainfall Rate Prediction

Rainfall rate forecasting plays an important role in various human activities. Rainfall forecasting is a challenging task due to the uncertainty of natural phenomena. In this paper, two neural network models are proposed for monthly rainfall rate forecasting. The performance of the proposed model is...

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Bibliographic Details
Published in:IOP conference series. Materials Science and Engineering 2017-03, Vol.180 (1), p.12057
Main Authors: Purnomo, H D, Hartomo, K D, Prasetyo, S Y J
Format: Article
Language:English
Subjects:
Accuracy
Artificial neural networks
Forecasting
Mathematical models
Model accuracy
Neural networks
Rain
Rainfall
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Summary:Rainfall rate forecasting plays an important role in various human activities. Rainfall forecasting is a challenging task due to the uncertainty of natural phenomena. In this paper, two neural network models are proposed for monthly rainfall rate forecasting. The performance of the proposed model is assesses based on monthly rainfall rate in Ampel, Boyolali, from 2001-2013. The experiment results show that the accuracy of the first model is much better than the accuracy of the second model. Its average accuracy is just above 98%, while the accuracy of the second model is approximately 75%. In additional, both models tend to perform better when the fluctuation of rainfall is low.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/180/1/012057