ANN Approach for Existing Bridge Evaluation Based on Grid and Domain Knowledge

The development of a methodology for accurate and reliable condition assessment of existing bridges has become very important. This paper presents a method for estimating the status of RC beam bridges using an artificial neural network based on grid and domain knowledge, which can help bridge agency to determine the bridge state more systematically in comparison with the existing bridge risk assessment methodologies which require a large number of subjective judgments from bridge experts to build the complicated nonlinear relationships among the relative importance of attributes. As a conclusion, when the calculated bridge rating and evaluation time compared with the ANN method, it is proven that the proposed algorithm provided results similar to those obtained by experts, but can improve efficiency of bridge state assessment.