Neural Networks in Civil Engineering: A Review

Abstract

The Chapter provides an introduction to the diverse range of alternative artificial neural networks (ANNs) currently available and the types of application they have been adopted for in civil and structural engineering. The presentation is made with reference to a classification and decomposition of the main features of ANNs. An introduction is first provided of the essential features of a typical ANN, and its mode of operation. A brief graphical interpretation is presented to illustrate how ANNs model data, and to help gain insight to their scope of application, merits and drawbacks. An identification is then made of the different types of processing that can be performed at the neuron level, the lowest level in an ANN. This is followed by an identification of the different ways in which neurons can be combined into an integral processing device capable of solving non-trivial problems. The range of alternative function types that can be implemented by ANNs are then examined. Finally, a review is provided of the primary methods of developing/training ANNs to solve specific problems. At each stage in the chapter, relevant neural paradigms are referenced and areas of application in civil and structural engineering are identified.