Using Artificial Neural Networks Approach to Estimate Compressive Strength for Rubberized Concrete

Periodica Polytechnica: Civil Engineering - Hungary
doi 10.3311/ppci.11928
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Periodica Polytechnica Budapest University of Technology and Economics

Related search

Anticipating the Compressive Strength of Hydrated Lime Cement Concrete Using Artificial Neural Network Model

Civil Engineering Journal
2018English

Prediction of Rubberized Concrete Properties Using Artificial Neural Network and Fuzzy Logic

Construction and Building Materials
BuildingCivilConstructionStructural EngineeringMaterials Science
2008English

Probabilistic Modelling of Compressive Strength of Concrete Using Response Surface Methodology and Neural Networks

Arabian Journal for Science and Engineering
Multidisciplinary
2014English

Prediction of Concrete Strength Containing Different Aggregates Through Artificial Neural Networks

Journal of Engineering Geology
2015English

The Use of Non-Destructive Tests to Estimate Self-Compacting Concrete Compressive Strength

MATEC Web of Conferences
Materials ScienceEngineeringChemistry
2018English

Compressive Strength Prediction of Roller-Compacted Concrete Using Nondestructive Tests Through Artificial Intelligence

2017English

SIMD Architecture Approach to Artificial Neural Networks Realisation

2010English

Prediction of Compressive Strength of Plain Concrete Confined With Ferrocement Using Artificial Neural Network (ANN) and Comparison With Existing Mathematical Models

American Journal of Civil Engineering and Architecture
2013English

Predicting Compressive Strength of Recycled Concrete for Construction 3D Printing Based on Statistical Analysis of Various Neural Networks

Journal of Building Construction and Planning Research
2018English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2025 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy