Developing a brain inspired multilobar neural networks architecture for rapidly and accurately estimating concrete compressive strength

Developing a brain inspired multilobar neural networks architecture for rapidly and accurately estimating concrete compressive strength

Abstract Concrete compressive strength is a critical parameter in construction and structural engineering. Destructive experimental methods that offer a reliable approach to obtaining this property involve time-consuming procedures. Recent advancements in artificial neural networks (ANNs) have shown...

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Bibliographic Details
Main Authors: Bashar Alibrahim, Ahed Habib, Maan Habib
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Artificial neural networks
Multi-lobar architecture
Data processing
Concrete compressive strength
Neural network optimization
Online Access:https://doi.org/10.1038/s41598-024-84325-z
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