Condition state evaluation of existing reinforced concrete bridges using neuro-fuzzy hybrid system

Abstract

This article presents a new approach for developing a concrete bridge rating expert system for deteriorated concrete bridges, constructed from multi-layer neural networks. The system evaluates the performance of concrete bridges on the basis of a simple visual inspection and technical specifications. The main reason of applying the neural network is that it performs fuzzy inference in the network, facilitates refinement of the knowledge base by use of the back-propagation method, and prevents not only the inference mechanism of the expert system but also the knowledge base after machine learning from becoming a black box.