Development of ANN model for discharge prediction and optimal design of sharp-crested triangular plan form weir for maximum discharge using linked ANN–optimization model

Triangular plan form weirs are advantageous over a normal weir in two ways. Within the limited channel width, use of such a weir increases the crest length and hence for a given head, increases the discharge and for a given discharge, reduces the head in comparison with a normal weir. In a previous...

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Autores principales:	Md. Ayaz, Talib Mansoor
Formato:	article
Lenguaje:	EN
Publicado:	IWA Publishing 2021
Materias:	artificial neural network discharge coefficient discharge measurement optimization triangular plan form weir Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506
Acceso en línea:	https://doaj.org/article/79e7af7e67ec45cda1db03ec78776129
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spelling	oai:doaj.org-article:79e7af7e67ec45cda1db03ec787761292021-11-06T10:08:34ZDevelopment of ANN model for discharge prediction and optimal design of sharp-crested triangular plan form weir for maximum discharge using linked ANN–optimization model1606-97491607-079810.2166/ws.2021.067https://doaj.org/article/79e7af7e67ec45cda1db03ec787761292021-09-01T00:00:00Zhttp://ws.iwaponline.com/content/21/6/3027https://doaj.org/toc/1606-9749https://doaj.org/toc/1607-0798Triangular plan form weirs are advantageous over a normal weir in two ways. Within the limited channel width, use of such a weir increases the crest length and hence for a given head, increases the discharge and for a given discharge, reduces the head in comparison with a normal weir. In a previous study, researchers proposed an empirical equation to compute the discharge coefficient of a triangular plan form weir. The prediction error on the discharge coefficient was ±7% from the line of agreement. In the present study, an ANN model has been utilized to train randomly selected 70% data, with 15% tested and validation made for the remaining 15% data. The model predicts the discharge coefficient with a prediction error in the range of ±2.5% from the line of agreement, thereby decreasing the prediction error in Cd by 64%. Also, the sensitivity analysis of the developed ANN model has been performed for all the parameters (weir height, skew weir length and flow depth) involved in the study and the weir height was found to be the most sensitive parameter. Furthermore, the linked ANN–optimization model has been developed to find the optimal values of design parameters of a triangular plan form weir for maximum discharge. HIGHLIGHTS The developed ANN model shows significant improvement in the estimation of discharge coefficient and reduces the prediction error in Cd by 64%.; The ANN model appears to be robust even for large random error levels up to 10% in the input parameters.; Linked ANN–optimization model has been developed to find the optimal values of design parameters of weir L, w and h for which the discharge Q is maximum.;Md. AyazTalib MansoorIWA Publishingarticleartificial neural networkdischarge coefficientdischarge measurementoptimizationtriangular plan form weirWater supply for domestic and industrial purposesTD201-500River, lake, and water-supply engineering (General)TC401-506ENWater Supply, Vol 21, Iss 6, Pp 3027-3041 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	artificial neural network discharge coefficient discharge measurement optimization triangular plan form weir Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506
spellingShingle	artificial neural network discharge coefficient discharge measurement optimization triangular plan form weir Water supply for domestic and industrial purposes TD201-500 River, lake, and water-supply engineering (General) TC401-506 Md. Ayaz Talib Mansoor Development of ANN model for discharge prediction and optimal design of sharp-crested triangular plan form weir for maximum discharge using linked ANN–optimization model
description	Triangular plan form weirs are advantageous over a normal weir in two ways. Within the limited channel width, use of such a weir increases the crest length and hence for a given head, increases the discharge and for a given discharge, reduces the head in comparison with a normal weir. In a previous study, researchers proposed an empirical equation to compute the discharge coefficient of a triangular plan form weir. The prediction error on the discharge coefficient was ±7% from the line of agreement. In the present study, an ANN model has been utilized to train randomly selected 70% data, with 15% tested and validation made for the remaining 15% data. The model predicts the discharge coefficient with a prediction error in the range of ±2.5% from the line of agreement, thereby decreasing the prediction error in Cd by 64%. Also, the sensitivity analysis of the developed ANN model has been performed for all the parameters (weir height, skew weir length and flow depth) involved in the study and the weir height was found to be the most sensitive parameter. Furthermore, the linked ANN–optimization model has been developed to find the optimal values of design parameters of a triangular plan form weir for maximum discharge. HIGHLIGHTS The developed ANN model shows significant improvement in the estimation of discharge coefficient and reduces the prediction error in Cd by 64%.; The ANN model appears to be robust even for large random error levels up to 10% in the input parameters.; Linked ANN–optimization model has been developed to find the optimal values of design parameters of weir L, w and h for which the discharge Q is maximum.;
format	article
author	Md. Ayaz Talib Mansoor
author_facet	Md. Ayaz Talib Mansoor
author_sort	Md. Ayaz
title	Development of ANN model for discharge prediction and optimal design of sharp-crested triangular plan form weir for maximum discharge using linked ANN–optimization model
title_short	Development of ANN model for discharge prediction and optimal design of sharp-crested triangular plan form weir for maximum discharge using linked ANN–optimization model
title_full	Development of ANN model for discharge prediction and optimal design of sharp-crested triangular plan form weir for maximum discharge using linked ANN–optimization model
title_fullStr	Development of ANN model for discharge prediction and optimal design of sharp-crested triangular plan form weir for maximum discharge using linked ANN–optimization model
title_full_unstemmed	Development of ANN model for discharge prediction and optimal design of sharp-crested triangular plan form weir for maximum discharge using linked ANN–optimization model
title_sort	development of ann model for discharge prediction and optimal design of sharp-crested triangular plan form weir for maximum discharge using linked ann–optimization model
publisher	IWA Publishing
publishDate	2021
url	https://doaj.org/article/79e7af7e67ec45cda1db03ec78776129
work_keys_str_mv	AT mdayaz developmentofannmodelfordischargepredictionandoptimaldesignofsharpcrestedtriangularplanformweirformaximumdischargeusinglinkedannoptimizationmodel AT talibmansoor developmentofannmodelfordischargepredictionandoptimaldesignofsharpcrestedtriangularplanformweirformaximumdischargeusinglinkedannoptimizationmodel
_version_	1718443804357296128

Development of ANN model for discharge prediction and optimal design of sharp-crested triangular plan form weir for maximum discharge using linked ANN–optimization model

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