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Uncertainty often recurs in structural system characterization as well as in choosing the mechanical model and in calibrating it. When analyzing a structure founded in cohesionless soils, the uncertainty in system modeling comes from soil inherent variability, site conditions, construction tolerance, and failure mechanisms. In this research, a Fuzzy-Neural Network method to predict the behavior of structures built on complex cohesionless soils is proposed. The method is based on an ArtificialNeural Network (ANN) for modeling the soil-foundation interaction. Its learning process analyzes over 200 records of building foundations, tanks, and embankments settlements on sand and gravel. Once validated, ANN is introduced in the soil-foundation-sovrastructure interaction model. Using fuzzy sets to define vague and ambiguous variables, the Fuzzy-Neural Network method predicts the system behavior and quantifies the uncertainty of its response. A numerical example shows the method effectiveness in the case of uncertainty in soil parameters and gives suggestions for successive applications.

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