Efficacy of ANFIS-GOA technique in flood prediction: a case study of Mahanadi river basin in India

Accurateness in flood prediction is of utmost significance for mitigating catastrophes caused by flood events. Flooding leads to severe civic and financial damage, particularly in large river basins, and mainly affects the downstream regions of a river bed. Artificial Intelligence (AI) models have b...

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Autores principales:	Abinash Sahoo, Sandeep Samantaray, Siddhartha Paul
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	anfis-goa anfis-gwo flood hydrological system modelling River, lake, and water-supply engineering (General) TC401-506 Water supply for domestic and industrial purposes TD201-500
Acceso en línea:	https://doaj.org/article/954a1ec0736346bd9b1edd10bbbce762
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id	oai:doaj.org-article:954a1ec0736346bd9b1edd10bbbce762
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spelling	oai:doaj.org-article:954a1ec0736346bd9b1edd10bbbce7622021-11-08T07:59:41ZEfficacy of ANFIS-GOA technique in flood prediction: a case study of Mahanadi river basin in India2616-651810.2166/h2oj.2021.090https://doaj.org/article/954a1ec0736346bd9b1edd10bbbce7622021-01-01T00:00:00Zhttp://doi.org/10.2166/h2oj.2021.090https://doaj.org/toc/2616-6518Accurateness in flood prediction is of utmost significance for mitigating catastrophes caused by flood events. Flooding leads to severe civic and financial damage, particularly in large river basins, and mainly affects the downstream regions of a river bed. Artificial Intelligence (AI) models have been effectively utilized as a tool for modelling numerous nonlinear relationships and is suitable to model complex hydrological systems. Therefore, the main purpose of this research is to propose an effective hybrid system by integrating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with meta-heuristic Grey Wolf Optimization (GWO) and Grasshopper Optimization Algorithm (GOA) for flood prediction in River Mahanadi, India. Robustness of proposed meta-heurestics are assessed by comparing with a conventional ANFIS model focusing on various input combinations considering 50 years of monthly historical flood discharge data. The potential of the AI models is evaluated and compared with observed data in both training and validation sets based on three statistical performance evaluation factors, namely root mean squared error (RMSE), mean squared error (MSE) and Wilmott Index (WI). Results reveal that robust ANFIS-GOA outperforms standalone AI techniques and can make superior flood forecasting for all input scenarios. HIGHLIGHTS A novel insight on prediction of flood flow is developed by hybridizing ANFIS-GOA.; Different input combinations of flood causative factors are analysed.; A comprehensive assessment and comparative analysis have been carried out.; Integrated artificial intelligence with GOA outperforms the standard AI methods.; ANFIS-GOA model exhibits a superior reliable model and improves the predictive precision of flood events.;Abinash SahooSandeep SamantaraySiddhartha PaulIWA Publishingarticleanfis-goaanfis-gwofloodhydrological systemmodellingRiver, lake, and water-supply engineering (General)TC401-506Water supply for domestic and industrial purposesTD201-500ENH2Open Journal, Vol 4, Iss 1, Pp 137-156 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	anfis-goa anfis-gwo flood hydrological system modelling River, lake, and water-supply engineering (General) TC401-506 Water supply for domestic and industrial purposes TD201-500
spellingShingle	anfis-goa anfis-gwo flood hydrological system modelling River, lake, and water-supply engineering (General) TC401-506 Water supply for domestic and industrial purposes TD201-500 Abinash Sahoo Sandeep Samantaray Siddhartha Paul Efficacy of ANFIS-GOA technique in flood prediction: a case study of Mahanadi river basin in India
description	Accurateness in flood prediction is of utmost significance for mitigating catastrophes caused by flood events. Flooding leads to severe civic and financial damage, particularly in large river basins, and mainly affects the downstream regions of a river bed. Artificial Intelligence (AI) models have been effectively utilized as a tool for modelling numerous nonlinear relationships and is suitable to model complex hydrological systems. Therefore, the main purpose of this research is to propose an effective hybrid system by integrating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with meta-heuristic Grey Wolf Optimization (GWO) and Grasshopper Optimization Algorithm (GOA) for flood prediction in River Mahanadi, India. Robustness of proposed meta-heurestics are assessed by comparing with a conventional ANFIS model focusing on various input combinations considering 50 years of monthly historical flood discharge data. The potential of the AI models is evaluated and compared with observed data in both training and validation sets based on three statistical performance evaluation factors, namely root mean squared error (RMSE), mean squared error (MSE) and Wilmott Index (WI). Results reveal that robust ANFIS-GOA outperforms standalone AI techniques and can make superior flood forecasting for all input scenarios. HIGHLIGHTS A novel insight on prediction of flood flow is developed by hybridizing ANFIS-GOA.; Different input combinations of flood causative factors are analysed.; A comprehensive assessment and comparative analysis have been carried out.; Integrated artificial intelligence with GOA outperforms the standard AI methods.; ANFIS-GOA model exhibits a superior reliable model and improves the predictive precision of flood events.;
format	article
author	Abinash Sahoo Sandeep Samantaray Siddhartha Paul
author_facet	Abinash Sahoo Sandeep Samantaray Siddhartha Paul
author_sort	Abinash Sahoo
title	Efficacy of ANFIS-GOA technique in flood prediction: a case study of Mahanadi river basin in India
title_short	Efficacy of ANFIS-GOA technique in flood prediction: a case study of Mahanadi river basin in India
title_full	Efficacy of ANFIS-GOA technique in flood prediction: a case study of Mahanadi river basin in India
title_fullStr	Efficacy of ANFIS-GOA technique in flood prediction: a case study of Mahanadi river basin in India
title_full_unstemmed	Efficacy of ANFIS-GOA technique in flood prediction: a case study of Mahanadi river basin in India
title_sort	efficacy of anfis-goa technique in flood prediction: a case study of mahanadi river basin in india
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/954a1ec0736346bd9b1edd10bbbce762
work_keys_str_mv	AT abinashsahoo efficacyofanfisgoatechniqueinfloodpredictionacasestudyofmahanadiriverbasininindia AT sandeepsamantaray efficacyofanfisgoatechniqueinfloodpredictionacasestudyofmahanadiriverbasininindia AT siddharthapaul efficacyofanfisgoatechniqueinfloodpredictionacasestudyofmahanadiriverbasininindia
_version_	1718442833513283584

Efficacy of ANFIS-GOA technique in flood prediction: a case study of Mahanadi river basin in India

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