The use of radial basis function and non-linear autoregressive exogenous neural networks to forecast multi-step ahead of time flood water level

International Journal of Advances in Intelligent Informatics

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Field Value
 
Title The use of radial basis function and non-linear autoregressive exogenous neural networks to forecast multi-step ahead of time flood water level
 
Creator Faruq, Amrul
Abdullah, Shahrum Shah
Marto, Aminaton
Abu Bakar, Mohd Anuar
Mohd Hussein, Shamsul Faisal
Che Razali, Che Munira
 
Subject Floods; Forecasting; Radial basis function; NARX; Artificial neural networks
 
Description Many different Artificial Neural Networks (ANN) models of flood have been developed for forecast updating. However, the model performance, and error prediction in which forecast outputs are adjusted directly based on models calibrated to the time series of differences between observed and forecast values, are very interesting and challenging task. This paper presents an improved lead time flood forecasting using Non-linear Auto Regressive Exogenous Neural Network (NARXNN), which shows better performance in term of forecast precision and produces minimum error compared to neural network method using Radial Basis Function (RBF) in examined 12-hour ahead of time. First, RBF forecasting model was employed to predict the flood water level of Kelantan River at Kuala Krai, Kelantan, Malaysia. The model is tested for 1-hour and 7-hour ahead of time water level at flood location. The same analysis has also been taken by NARXNN method. Then, a non-linear neural network model with exogenous input promoted with enhancing a forecast lead time to 12-hour. Both about the performance comparison has briefly been analyzed. The result verified the precision of error prediction of the presented flood forecasting model.
 
Publisher Universitas Ahmad Dahlan
 
Contributor
 
Date 2019-03-31
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

 
Format application/pdf
 
Identifier http://ijain.org/index.php/IJAIN/article/view/280
10.26555/ijain.v5i1.280
 
Source International Journal of Advances in Intelligent Informatics; Vol 5, No 1 (2019): March 2019; 1-10
2548-3161
2442-6571
 
Language eng
 
Relation http://ijain.org/index.php/IJAIN/article/view/280/ijain_v5i1_p1-10
 
Rights https://creativecommons.org/licenses/by-sa/4.0
 

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