It is vital that design engineers effectively forecast the local scourge around the pier as precisely as possible because an excess of local scouring around the pier unbalances and breaks down the pier. Local scouring around a bridge's piers is one of the most common causes of bridge failure, possibly resulting in significant economic and human losses. However, due to the various elements that go into this process, predicting the exact depth of local scouring is challenging. The major goal of this research is to develop an empirical formula for predicting the local depth of scouring around a bridge pier using gene expression programming (GEP), a contemporary fine computing modeling approach, and artificial neural networks (ANN). The empirical equations were derived using a variety of critical factors, including pier form, flow depth, flow intensity, pier width, Froude number Fr, abutment protrusion length L, abutment protrusion width, discharge, and flow direction angle. All of these factors were derived from the problem's dimensional and non-dimensional analysis. Several trials were conducted for two case studies to predict an empirical formula each trial had a different statistical measurement predict using DTREG and each trial had modified model building parameters, fifteen different trials were conducted.
Anahtar Kelimeler: Artificial Neural Network (ANN), Gene Expression Programming (GEP), Bridge piers, Scour depth prediction
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