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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Vydáno v:	ACI materials journal Ročník 118; číslo 4; s. 91 - 96
Hlavní autoři:	Bhogayata, Ankur, Kakadiya, Sneh, Makwana, Rinkesh
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Farmington Hills American Concrete Institute 01.07.2021
Témata:	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
On-line přístup:	Získat plný text
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