Abstract
This paper presents the use of two artificial intelligence modeling methods, namely genetic programming (GP) and adaptive neuro-fuzzy inference system (ANFIS), to predict pier scour depth based on clear water conditions of 320 data sets of laboratory and field data measurements. The scour depth was modeled as a function of five main dimensionless parameters: pier width, approaching flow depth, Froude number, standard deviation of grain size distribution, and channel open ratio. A functional relationship was established using the trained GP model, and its performance was verified by comparing the results with those obtained by the ANFIS model and seven conventional regression-based formulas. Numerical tests indicated that the GP model yielded much superior agreement than the ANFIS model or any other empirical equation. The advantage of the GP model was confirmed by applying the derived GP equation to predict the scour depth around the piers of Imbaba Bridge, Egypt.
Highlights
Bridge scour is the result of the erosive action of flowing water, excavating and carrying away material from the bed and banks of streams and from around the piers and abutments of bridges (Richardson and Davis 2001)
The results indicated that the genetic programming (GP) model (Eq 15) has a superior performance to the adaptive neuro-fuzzy inference system (ANFIS) model and the empirical pier scour equations furnished in "Conventional regression models" section for all the experimental data considered
This paper investigated the use of both ANFIS and GP-based inductive models for predicting relative bridge pier scour depth utilizing previously collected laboratory and field data, and their performance was compared with regression-based models
Summary
Bridge scour is the result of the erosive action of flowing water, excavating and carrying away material from the bed and banks of streams and from around the piers and abutments of bridges (Richardson and Davis 2001). Applied Water Science (2020) 10:57 model studies of local scour In this context, several reviews summarized equations for pier scour depths in Breusers et al (1977), Dey (1997), and Melville and Sutherland (1988). When applying the existing empirical equations for predicting bridge pier scour to field cases, the scour depths are overpredicted (BabaeyanKoopaei and Valentine 1999). This means increased construction and maintenance costs as the foundation levels are required to be deeper than it should be
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