Applications of neural networks to produce optimum designs

Abstract

An artificial neural network can be considered as an information processing system where the architecture essentially mimics the biological system of the brain. A neural network consists of a number of interconnecting processing units referred to as neurons. Each of these connections has numerical weights associated with them. These weights determine the nature and strength of the influence between the interconnected neurons. The neural network can be trained by using a suitable set of data. The trained network can be tested for its performance. When the performance is adequate, the net can be used to make predictions for new cases. Neural networks have been successfully used in many disciplines on engineering such as in many civil engineering applications (Goh, 1994), prediction of pile capacities (Chow et al., 1995), Multi-objective and multirecourse decision support systems (Wei & Singh, 1995), Control systems (Macnab & D’Elenterio, 1995) etc.