Artificial Neural Networks to Predict the Mechanical Properties of Natural Fibre-Reinforced Compressed Earth Blocks (CEBs)

被引：15

作者：

Turco, Chiara ^{[1
]}

Funari, Marco Francesco ^{[1
]}

Teixeira, Elisabete ^{[1
]}

Mateus, Ricardo ^{[1
]}

机构：

[1] Univ Minho, Dept Civil Engn, ISISE, P-4800058 Guimaraes, Portugal

来源：

FIBERS | 2021年 / 9卷 / 12期

关键词：

Compressed Earth Blocks; natural fibres; reinforcement; compressive strength; tensile strength; Artificial Neural Networks; FLEXURAL STRENGTH; SOIL BLOCKS; CONCRETE; CONSTRUCTION; PERFORMANCE; MASONRY; DESIGN; SILICA; SHELL;

D O I：

10.3390/fib9120078

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The purpose of this study is to explore Artificial Neural Networks (ANNs) to predict the compressive and tensile strengths of natural fibre-reinforced Compressed Earth Blocks (CEBs). To this end, a database was created by collecting data from the available literature. Data relating to 332 specimens (Database 1) were used for the prediction of the compressive strength (ANN1), and, due to the lack of some information, those relating to 130 specimens (Database 2) were used for the prediction of the tensile strength (ANN2). The developed tools showed high accuracy, i.e., correlation coefficients (R-value) equal to 0.97 for ANN1 and 0.91 for ANN2. Such promising results prompt their applicability for the design and orientation of experimental campaigns and support numerical investigations.

引用

页数：21

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