Neural Network for Mixture Design Optimization of Geopolymer Concrete

The paper discusses the development and application of the artificial neural network (ANN) model for predicting the compressive and splitting tensile strength of the geopolymer-based concrete composites (GPC). The strength properties of GPC are influenced by the proportions of the constituents--name...

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Veröffentlicht in:	ACI materials journal Jg. 118; H. 4; S. 91 - 96
Hauptverfasser:	Bhogayata, Ankur, Kakadiya, Sneh, Makwana, Rinkesh
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Farmington Hills American Concrete Institute 01.07.2021
Schlagworte:	Accuracy Algorithms Artificial intelligence Artificial neural networks Back propagation Back propagation networks Caustic soda Cement Chemical properties Compressive strength Concrete Constituents Data collection Data processing Datasets Design optimization Fly ash Fuzzy logic Geopolymers Literature reviews Mathematical optimization Mechanical properties Neural networks Operators (mathematics) Optimization techniques Tensile strength Variables India
ISSN:	0889-325X, 0889-325X, 1944-737X
Online-Zugang:	Volltext
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