Prediction of Concrete Properities Using Neural Networks
To design or optimise concrete mix composition, a mapping is needed from one multidimensional space of the input data into another multidimensional space of the output data. The analytical form of such transformation of the data preserved in various experimental databases is not known. Artificial Neural Network (ANN) is an alternative to using analytical description. Fuzzy ARTMAP - one particular type of ANN was adapted and trained using three different databases to predict concrete properties of strength, workability or cost. The results are encouraging. If properly trained, that is if learning is conducted at appropriate setting of the system parameters, Fuzzy ARTMAP will be able to provide correct predictions. Unlike the case of some other networks and statistical "models", which even in critical cases try to give complete predictions, often of poor accuracy or even totally incorrect, the Fuzzy ARTMAP gives no prediction at all for very non-typical records, which to certain extent protects the user from misinterpretation of the data.
G.A. CARPENTER, S. GROSSBERG, N. MARJ
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