Bridge Condition Deterioration Prediction Using the Whale Optimization Algorithm and Extreme Learning Machine

Abstract

To address the problem in model computations and the limited accuracy of current bridge deterioration prediction methods, this paper proposes a novel bridge deterioration prediction meth-od using the whale optimization algorithm and extreme learning machine (WOA-ELM). First, we collected a dataset consisting of 539 sets of bridge inspection data and determined the necessary influencing factors through correlation analysis. Subsequently, the WOA-ELM algorithm was applied to establish a nonlinear mapping relationship between each influencing factor and the bridge condition indicators. Furthermore, the extreme learning machine (ELM), back-propagation neural network (BPNN), decision trees (DT), and support vector machine (SVM) were employed for comparison to validate the superiority of the proposed method. In addition, this paper provides further substantiation of the model’s exceptional predictive capabilities across diverse bridge components. The results demonstrate the accurate predictive capability of the proposed method for bridge conditions. Compared with ELM, BPNN, DT, and SVM, the proposed method exhibits significant improvements in predictive accuracy, i.e., the correlation coefficient is increased by 4.1%, 11.4%, 24.5%, and 33.6%, and the root mean square error is reduced by 7.3%, 18.0%, 14.8%, and 18.1%, respectively. Moreover, the proposed method presents considerably enhanced generalization capabilities, resulting in the reduction in mean relative error by 11.6%, 15.3%, 6%, and 16.2%. The proposed method presents a robust framework for proactive bridge maintenance.

Stacking Ensemble-Based Machine Learning Model for Predicting Deterioration Components of Steel W-Section Beams

“…Jiang et al [27] obtained the deterioration of a bridge through the hybrid method of whale algorithm with other machine learning. The results demonstrated that the com-bined model performed better than the simple model.…”