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Introduction to artificial neural systems
Introduction to artificial neural systems
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Advances in Engineering Software
Advances in Engineering Software
Advances in Engineering Software
Review: Estimation of California bearing ratio by using soft computing systems
Expert Systems with Applications: An International Journal
Aseismic ability estimation of school building using predictive data mining models
Expert Systems with Applications: An International Journal
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This paper details the development of neural network models that provide effective predictive capability in respect of the workability of concrete incorporating metakaolin (MK) and fly ash (FA). The predictions produced reflect the effect of graduated variations in pozzolanic replacement in Portland cement (PC) of up to 15% MK and 40% FA. The results show that the models are reliable and accurate and illustrate how neural networks can be used to beneficially predict the workability parameters of slump, compacting factor and Vebe time across a wide range of PC-FA-MK compositions.