Concrete strength prediction by means of neural network

摘要

In this article a model is developed, based on neurocomputing, for predicting, with sufficient approxi- mation, the compressive strength of cement conglomerates. First, the principles of conncectionism are briefly recalled. Some neural networks are then constructed in which the different mix-design parameters of a variety of cement conglomerates, i. e. the compressive strength, are associated. The experimental data obtained during construction of the 'Alto Sulcis Thermal Power Station' at Por- tovesme, ltaly, were used in the tests. The availability of a substantial amount of data enadbled the method to be suitably calibrated and satisfactory results were obtained for evaluating the mechanical properties of different concrete mixes.