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Prediction of concrete compressive strength through artificial neural networks
Concrete properties, including its compressive strength, are in general highly nonlinear functions of its components. Concrete mix design methods are basically simulations that require costly and time consuming adjustments in laboratory. A useful support tool based on artificial neural networks, using a multilayer perceptron network, is proposed in this paper as a means to predict compressive strength of concrete mixes. The developed models are useful for reducing the quantity of laboratory tests required for concrete mix design adjustments.
Prediction of concrete compressive strength through artificial neural networks
Concrete properties, including its compressive strength, are in general highly nonlinear functions of its components. Concrete mix design methods are basically simulations that require costly and time consuming adjustments in laboratory. A useful support tool based on artificial neural networks, using a multilayer perceptron network, is proposed in this paper as a means to predict compressive strength of concrete mixes. The developed models are useful for reducing the quantity of laboratory tests required for concrete mix design adjustments.
Prediction of concrete compressive strength through artificial neural networks
Pablo Neira (author) / Leonardo Bennun (author) / Mauricio Pradena (author) / Jaime Gomez (author)
2020
Article (Journal)
Electronic Resource
Unknown
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