Enhancement of nitrogen prediction accuracy through a new hybrid model using ant colony optimization and an Elman neural network

Advanced human activities, including modern agricultural practices, are responsible for alteration of natural concentration of nitrogen compounds in rivers. Future prediction of nitrogen compound concentrations (especially nitrate-nitrogen and ammonia-nitrogen) are important for countries where hous...

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Autores principales:	Pavitra Kumar, Sai Hin Lai, Nuruol Syuhadaa Mohd, Md Rowshon Kamal, Ali Najah Ahmed, Mohsen Sherif, Ahmed Sefelnasr, Ahmed El-shafie
Formato:	article
Lenguaje:	EN
Publicado:	Taylor & Francis Group 2021
Materias:	nitrate-nitrogen ammonia-nitrogen ant colony optimization elman neural network new aco-enn hybrid model Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/5a3f19aa14ee4a40a623018cec27c938
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spelling	oai:doaj.org-article:5a3f19aa14ee4a40a623018cec27c9382021-11-26T11:19:48ZEnhancement of nitrogen prediction accuracy through a new hybrid model using ant colony optimization and an Elman neural network1994-20601997-003X10.1080/19942060.2021.1990134https://doaj.org/article/5a3f19aa14ee4a40a623018cec27c9382021-01-01T00:00:00Zhttp://dx.doi.org/10.1080/19942060.2021.1990134https://doaj.org/toc/1994-2060https://doaj.org/toc/1997-003XAdvanced human activities, including modern agricultural practices, are responsible for alteration of natural concentration of nitrogen compounds in rivers. Future prediction of nitrogen compound concentrations (especially nitrate-nitrogen and ammonia-nitrogen) are important for countries where household water is obtained from rivers after treatment. Increased concentrations of nitrogen compounds result in the suspension of household water supplies. Artificial Neural Networks (ANNs) have already been deployed for the prediction of nitrogen compounds in various countries. But standalone ANN have several limitations. However, the limitations of ANNs can be resolved using hybrid models. This study proposes a new ACO-ENN hybrid model developed by integrating Ant Colony Optimization (ACO) with an Elman Neural Network (ENN). The developed ACO-ENN hybrid model was used to improve the prediction results of nitrate-nitrogen and ammonia-nitrogen prediction models. The results of new hybrid models were compared with multilayer ANN models and standalone ENN models. There was a significant improvement in the mean square errors (MSE) (0.196→0.049→0.012, i.e. ANN→ENN→Hybrid), mean absolute errors (MAE) (0.271→0.094→0.069) and Nash–Sutcliffe efficiencies (NSE) (0.7255→0.9321→0.984). The hybrid model had outstanding performance compared with the ANN and ENN models. Hence, the prediction accuracy of nitrate-nitrogen and ammonia-nitrogen has been improved using new ACO-ENN hybrid model.Pavitra KumarSai Hin LaiNuruol Syuhadaa MohdMd Rowshon KamalAli Najah AhmedMohsen SherifAhmed SefelnasrAhmed El-shafieTaylor & Francis Grouparticlenitrate-nitrogenammonia-nitrogenant colony optimizationelman neural networknew aco-enn hybrid modelEngineering (General). Civil engineering (General)TA1-2040ENEngineering Applications of Computational Fluid Mechanics, Vol 15, Iss 1, Pp 1843-1867 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	nitrate-nitrogen ammonia-nitrogen ant colony optimization elman neural network new aco-enn hybrid model Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	nitrate-nitrogen ammonia-nitrogen ant colony optimization elman neural network new aco-enn hybrid model Engineering (General). Civil engineering (General) TA1-2040 Pavitra Kumar Sai Hin Lai Nuruol Syuhadaa Mohd Md Rowshon Kamal Ali Najah Ahmed Mohsen Sherif Ahmed Sefelnasr Ahmed El-shafie Enhancement of nitrogen prediction accuracy through a new hybrid model using ant colony optimization and an Elman neural network
description	Advanced human activities, including modern agricultural practices, are responsible for alteration of natural concentration of nitrogen compounds in rivers. Future prediction of nitrogen compound concentrations (especially nitrate-nitrogen and ammonia-nitrogen) are important for countries where household water is obtained from rivers after treatment. Increased concentrations of nitrogen compounds result in the suspension of household water supplies. Artificial Neural Networks (ANNs) have already been deployed for the prediction of nitrogen compounds in various countries. But standalone ANN have several limitations. However, the limitations of ANNs can be resolved using hybrid models. This study proposes a new ACO-ENN hybrid model developed by integrating Ant Colony Optimization (ACO) with an Elman Neural Network (ENN). The developed ACO-ENN hybrid model was used to improve the prediction results of nitrate-nitrogen and ammonia-nitrogen prediction models. The results of new hybrid models were compared with multilayer ANN models and standalone ENN models. There was a significant improvement in the mean square errors (MSE) (0.196→0.049→0.012, i.e. ANN→ENN→Hybrid), mean absolute errors (MAE) (0.271→0.094→0.069) and Nash–Sutcliffe efficiencies (NSE) (0.7255→0.9321→0.984). The hybrid model had outstanding performance compared with the ANN and ENN models. Hence, the prediction accuracy of nitrate-nitrogen and ammonia-nitrogen has been improved using new ACO-ENN hybrid model.
format	article
author	Pavitra Kumar Sai Hin Lai Nuruol Syuhadaa Mohd Md Rowshon Kamal Ali Najah Ahmed Mohsen Sherif Ahmed Sefelnasr Ahmed El-shafie
author_facet	Pavitra Kumar Sai Hin Lai Nuruol Syuhadaa Mohd Md Rowshon Kamal Ali Najah Ahmed Mohsen Sherif Ahmed Sefelnasr Ahmed El-shafie
author_sort	Pavitra Kumar
title	Enhancement of nitrogen prediction accuracy through a new hybrid model using ant colony optimization and an Elman neural network
title_short	Enhancement of nitrogen prediction accuracy through a new hybrid model using ant colony optimization and an Elman neural network
title_full	Enhancement of nitrogen prediction accuracy through a new hybrid model using ant colony optimization and an Elman neural network
title_fullStr	Enhancement of nitrogen prediction accuracy through a new hybrid model using ant colony optimization and an Elman neural network
title_full_unstemmed	Enhancement of nitrogen prediction accuracy through a new hybrid model using ant colony optimization and an Elman neural network
title_sort	enhancement of nitrogen prediction accuracy through a new hybrid model using ant colony optimization and an elman neural network
publisher	Taylor & Francis Group
publishDate	2021
url	https://doaj.org/article/5a3f19aa14ee4a40a623018cec27c938
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_version_	1718409471521193984

Enhancement of nitrogen prediction accuracy through a new hybrid model using ant colony optimization and an Elman neural network

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