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» Articles » PMID: 28598400

Feed-Forward Neural Network Prediction of the Mechanical Properties of Sandcrete Materials

Overview
Journal Sensors (Basel)
Publisher MDPI
Specialty Biotechnology
Date 2017 Jun 10
PMID 28598400
Citations 15
Authors
Panagiotis G Asteris
Panayiotis C Roussis
Maria G Douvika
Affiliations
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Abstract

This work presents a soft-sensor approach for estimating critical mechanical properties of sandcrete materials. Feed-forward (FF) artificial neural network (ANN) models are employed for building soft-sensors able to predict the 28-day compressive strength and the modulus of elasticity of sandcrete materials. To this end, a new normalization technique for the pre-processing of data is proposed. The comparison of the derived results with the available experimental data demonstrates the capability of FF ANNs to predict with pinpoint accuracy the mechanical properties of sandcrete materials. Furthermore, the proposed normalization technique has been proven effective and robust compared to other normalization techniques available in the literature.

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