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Compressive strength prediction of rice husk ash using multiphysics genetic expression programming

Rice husk ash (RHA) is obtained by burning rice husks. An advanced programming technique known as genetic expression programming (GEP) is used in this research for developing an empirical multiphysics model for predicting the compressive strength of RHA incorporated concrete. A vast database compris...

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Main Authors:	Aslam, F., Elkotb, M.A., Iqtidar, A., Khan, M.A., Javed, M.F., Usanova, K.I., Khan, M.I., Alamri, S., Musarat, M.A.
Format:	Article
Published:	Ain Shams University 2022
Online Access:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118766459&doi=10.1016%2fj.asej.2021.09.020&partnerID=40&md5=87657372a1959d8b9e651dc0d9b883e5 http://eprints.utp.edu.my/33131/
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spelling	my.utp.eprints.331312022-07-06T07:56:18Z Compressive strength prediction of rice husk ash using multiphysics genetic expression programming Aslam, F. Elkotb, M.A. Iqtidar, A. Khan, M.A. Javed, M.F. Usanova, K.I. Khan, M.I. Alamri, S. Musarat, M.A. Rice husk ash (RHA) is obtained by burning rice husks. An advanced programming technique known as genetic expression programming (GEP) is used in this research for developing an empirical multiphysics model for predicting the compressive strength of RHA incorporated concrete. A vast database comprising of 250 data points is obtained from the extensive and consistent literature review. Different parameters such as age, RHA content, cement content, water content, amount of superplasticizer and aggregate content are used as inputs. A closed-form equation solution was obtained to predict the compressive strength of RHA based on input parameters. The performance of GEP is evaluated by comparing it with regression models. Statistical parameter R2 is used to assess the results predicted by GEP and regression models. Statistical and parametric analysis is also carried out to determine the influence of inputs on the outcome. The GEP model performed better in all terms as compared to other models. Â© 2021 THE AUTHORS Ain Shams University 2022 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118766459&doi=10.1016%2fj.asej.2021.09.020&partnerID=40&md5=87657372a1959d8b9e651dc0d9b883e5 Aslam, F. and Elkotb, M.A. and Iqtidar, A. and Khan, M.A. and Javed, M.F. and Usanova, K.I. and Khan, M.I. and Alamri, S. and Musarat, M.A. (2022) Compressive strength prediction of rice husk ash using multiphysics genetic expression programming. Ain Shams Engineering Journal, 13 (3). http://eprints.utp.edu.my/33131/
institution	Universiti Teknologi Petronas
building	UTP Resource Centre
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Petronas
content_source	UTP Institutional Repository
url_provider	http://eprints.utp.edu.my/
description	Rice husk ash (RHA) is obtained by burning rice husks. An advanced programming technique known as genetic expression programming (GEP) is used in this research for developing an empirical multiphysics model for predicting the compressive strength of RHA incorporated concrete. A vast database comprising of 250 data points is obtained from the extensive and consistent literature review. Different parameters such as age, RHA content, cement content, water content, amount of superplasticizer and aggregate content are used as inputs. A closed-form equation solution was obtained to predict the compressive strength of RHA based on input parameters. The performance of GEP is evaluated by comparing it with regression models. Statistical parameter R2 is used to assess the results predicted by GEP and regression models. Statistical and parametric analysis is also carried out to determine the influence of inputs on the outcome. The GEP model performed better in all terms as compared to other models. Â© 2021 THE AUTHORS
format	Article
author	Aslam, F. Elkotb, M.A. Iqtidar, A. Khan, M.A. Javed, M.F. Usanova, K.I. Khan, M.I. Alamri, S. Musarat, M.A.
spellingShingle	Aslam, F. Elkotb, M.A. Iqtidar, A. Khan, M.A. Javed, M.F. Usanova, K.I. Khan, M.I. Alamri, S. Musarat, M.A. Compressive strength prediction of rice husk ash using multiphysics genetic expression programming
author_facet	Aslam, F. Elkotb, M.A. Iqtidar, A. Khan, M.A. Javed, M.F. Usanova, K.I. Khan, M.I. Alamri, S. Musarat, M.A.
author_sort	Aslam, F.
title	Compressive strength prediction of rice husk ash using multiphysics genetic expression programming
title_short	Compressive strength prediction of rice husk ash using multiphysics genetic expression programming
title_full	Compressive strength prediction of rice husk ash using multiphysics genetic expression programming
title_fullStr	Compressive strength prediction of rice husk ash using multiphysics genetic expression programming
title_full_unstemmed	Compressive strength prediction of rice husk ash using multiphysics genetic expression programming
title_sort	compressive strength prediction of rice husk ash using multiphysics genetic expression programming
publisher	Ain Shams University
publishDate	2022
url	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118766459&doi=10.1016%2fj.asej.2021.09.020&partnerID=40&md5=87657372a1959d8b9e651dc0d9b883e5 http://eprints.utp.edu.my/33131/
_version_	1738657459557367808
score	13.211869

Compressive strength prediction of rice husk ash using multiphysics genetic expression programming

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