Artificial neural networks are algorithms for cognitive tasks, such as learning and optimization. They have the ability to learn and generalize from examples without knowledge of rules. Research into artificial neural networks and their application to structural engineering problems is gaining interest and is growing continuously. The use of artificial neural networks in structural engineering has evolved as a new computing paradigm, even though still very limited.

The objective of this paper is to introduce the concept, theoretical background, advantages, and shortcomings of artificial neural networks technology. The architecture and mathematics learning techniques used to train back-propagation neural networks are briefly described. Next, the state of the art on the application of artificial neural networks technology to structural engineering problems is presented. Then, a conclusion is drawn.

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