Determination of compressive strength of perlite-containing slag-based geopolymers and its prediction using artificial neural network and regression-based methods

ALAKARA, ERDİNÇ HALİS; NACAR, SİNAN; SEVİM, ÖZER; KORKMAZ, SERDAR; DEMİR, İLHAMİ

doi:10.1016/j.conbuildmat.2022.129518

Determination of compressive strength of perlite-containing slag-based geopolymers and its prediction using artificial neural network and regression-based methods

Yazarlar (5)
ERDİNÇ HALİS ALAKARA
SİNAN NACAR
ÖZER SEVİM
Dr. Öğr. Üyesi Serdar KORKMAZ Kurum Bilgileri Kaman Meslek Yüksekokulu İnşaat Yapı Denetimi Pr Özgeçmiş Sayfası İletişim Bilgileri: (386)280-5458 skorkmaz@ahievran.edu.tr Kırşehir Ahi Evran Üniversitesi, Türkiye
İLHAMİ DEMİR

Devamını Göster

Özet

This study has two main objectives: (i) to investigate the parameters affecting the compressive strength (CS) of perlite-containing slag-based geopolymers and (ii) to predict the CS values obtained from experimental studies. In this regard, 540 cubic geopolymer samples incorporating different raw perlite powder (RPP) replacement ratios, different sodium hydroxide (NaOH) molarity, different curing time, and different curing temperatures for a total of 180 mixture groups were produced and their CS results were experimentally determined. Then conventional regression analysis (CRA), multivariate adaptive regression splines (MARS), and TreeNet methods, as well as artificial neural network (ANN) methods, were used to predict the CS results of geopolymers using this experimentally obtained data set. Root mean square error (RMSE), mean absolute error (MAE), scatter index (SI) and Nash-Sutcliffe (NS) performance …

Anahtar Kelimeler

Makale Türü	Özgün Makale
Makale Alt Türü	SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale
Dergi Adı	Construction and Building Materials
Dergi ISSN	0950-0618 Wos Dergi Scopus Dergi
Dergi Tarandığı Indeksler	SCI-Expanded
Dergi Grubu	Q1
Makale Dili	Türkçe
Basım Tarihi	12-2022
Cilt No	359
Doi Numarası	10.1016/j.conbuildmat.2022.129518
Makale Linki	http://dx.doi.org/10.1016/j.conbuildmat.2022.129518

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Atıf Sayıları
Google Scholar	30

Determination of compressive strength of perlite-containing slag-based geopolymers and its prediction using artificial neural network and regression-based methods

Akademisyenler > Serdar KORKMAZ > Yayın Detayı

Determination of compressive strength of perlite-containing slag-based geopolymers and its prediction using artificial neural network and regression-based methods

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