Assessment and Prediction of Corrosion Rate of Marine Railway Bridges Based on Ridge Regression Model

This investigation employs ridge regression analysis to assess and forecast the corrosion rate of maritime railway bridges. We have gathered and organized pertinent data, devising a regression model encompassing multiple attributes, intending to scrutinize seawater’s influence on railway bridge corrosion. The model’s performance is appraised using cross-validation techniques, and the significance of each point is measured via ridge regression coefficients. Experimental findings demonstrate that the ridge regression model excels in predicting the corrosion rate of maritime railway bridges, exhibiting minimal discrepancies between predicted and actual values. Upon analysis of the model’s attributes, we discern that salinity and sulfide content in seawater are critical determinants of railway bridge corrosion rates. The findings of this study provide valuable reference points for marine engineering and railway bridge construction while offering novel insights into the application of ridge regression models for predicting and analyzing maritime environmental issues.