Artificial Intelligence Applications in Civil Engineering

Abstract

[...]LS-SVM has been identified as the better approach for the task of pothole detection with a desired accuracy of approximately 89%. According to R2 values, the best result in the models was obtained from BNN with 0.98 for the training set and from RBF with 0.85 for the test set. According to the demand from the constructors during the considered projects, 5 main criteria and 17 subcriteria were established for the selection of low-carbon suppliers in the construction sector. [...]the authors revealed that the proposed model can be easily extended to analyze other management decision problems as a structural model.