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Use of a Neural Network to Predict Strength and Optimum Compositions of Natural Alumina-Silica-Based Geopolymers
Dali Bondar
School of Natural and Built Environment
Research output
:
Contribution to journal
›
Article
›
peer-review
13
Citations (Scopus)
Overview
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Dive into the research topics of 'Use of a Neural Network to Predict Strength and Optimum Compositions of Natural Alumina-Silica-Based Geopolymers'. Together they form a unique fingerprint.
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Weight
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Engineering
Networks
100%
Geopolymer
100%
Feedforward
50%
Compressive Strength
33%
Products
33%
Architecture
33%
Chemical Composition
33%
Models
16%
Research
16%
Accuracy
16%
Mechanisms
16%
Validation
16%
Prediction
16%
Artificial Neural Network
16%
Simulators
16%
Activator
16%
Hidden Layer
16%
Backpropagation
16%
Hidden Neuron
16%
Geopolymerization
16%
Output Pattern
16%
Material Science
Mechanical Strength
100%
Aluminum Oxide
100%
Silicon Dioxide
100%
Geopolymers
100%
Compressive Strength
50%
Silicate
50%
Chemical Engineering
Alumina
100%
Silica
100%
Neural Network
100%
Silicate
66%
Backpropagation
33%
Activated Alumina
33%