Premium
A Fuzzy‐Neural Network Method for Modeling Uncertainties in Soil‐Structure Interaction Problems
Author(s) -
Provenzano P.
Publication year - 2003
Publication title -
computer‐aided civil and infrastructure engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.773
H-Index - 82
eISSN - 1467-8667
pISSN - 1093-9687
DOI - 10.1111/1467-8667.00326
Subject(s) - artificial neural network , fuzzy logic , foundation (evidence) , process (computing) , computer science , neuro fuzzy , civil engineering , geotechnical engineering , data mining , artificial intelligence , engineering , fuzzy control system , geography , archaeology , operating system
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 Artificial‐Neural 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.