Four-layer perceptron approach for strength prediction of UHPC
Joaquín Abellán García
Abstract
This research is aimed to develop a four-layer multi-layer-perceptron (MLP) model for predicting the compressive strength of ultra-high-performance concrete (UHPC), regardless of the combination of a wide range of supplementary cementitious materials (SCM) or the maximum size of aggregate used. UHPC is a high-tech type of concrete resulted of the mixture of several constituents. Therefore, the effect of each component and their interactions on compressive strength is more difficult to understand than in conventional concrete. A total of 210 own experimental campaign data added to 717 published work throughout the world data were used for training purposes by using the R-code language. To analyze the relationships between the UHPC’s components and strength, the Olden algorithm was used. The interpretation of both the statistical performance metrics and the results of Olden’s sensitivity analysis indicated that the proposed model was an efficient approach for predicting the compressive strength of UHPC. The trained MLP model can be used for forecasting the compressive strength for a given UHPC mixture design in quick time without performing any trial.