Optimizing the Weight of Steel Structures using Artificial Neural Network Method

Optimization is one of the most important issues in civil engineering. In this research, artificial neural network (ANN) has been used to optimize the structure of steel structures. The multilayer neural network of perceptron, one of the most widely used neural networks, has been used. Different structures of artificial neural network with different number of hidden layers and number of different neurons have been modeled to achieve the best architecture of artificial neural network model. Neural network models have acceptable success in the optimization process. Dimensional properties of structures have been used in all these models. Models used for optimization have four input parameters, one output parameter is used. A large set of structural models has been used as a database. In the perceptron neural network, networks with different architecture with one and two hidden layers have been used to determine the most accurate network. Extracting and presenting the relationships governing a neural network model gives the user more confidence in using such models, thus facilitating the application of such models in engineering work.