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Experimental and modelling of alkali-activated mortar compressive strength using hybrid support vector regression and genetic algorithm

This paper presents the outcome of work conducted to develop models for the prediction of compressive strength (CS) of alkali-activated limestone powder and natural pozzolan mortar (AALNM) using hybrid genetic algorithm (GA) and support vector regression (SVR) algorithm, for the first time. The deve...

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Bibliographic Details
Main Authors: Al-Sodani, Khaled A. Alawi, Adewumi, Adeshina Adewale, Mohd. Ariffin, Mohd. Azreen, Maslehuddin, Mohammed, Mohammad Ismail, Mohammad Ismail, Salami, Hamza Onoruoiza, Owolabi, Taoreed O., Mohamed, Hatim Dafalla
Format: Article
Language:English
Published: MDPI AG 2021
Subjects:
TA Engineering (General). Civil engineering (General)
Online Access:http://eprints.utm.my/id/eprint/97526/1/MohdAzreen2021_ExperimentalandModellingofAlkaliActivatedMortar.pdf
http://eprints.utm.my/id/eprint/97526/
http://dx.doi.org/10.3390/ma14113049
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http://eprints.utm.my/id/eprint/97526/1/MohdAzreen2021_ExperimentalandModellingofAlkaliActivatedMortar.pdf
http://eprints.utm.my/id/eprint/97526/
http://dx.doi.org/10.3390/ma14113049

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