A Cost Estimation Model for Repair Bridges Based on Artificial Neural Network

Abstract

Estimating the total cost of bridges repair and maintenance with high accuracy is an important components, and points to a need for a cost estimation model. This paper focuses on the development of a more accurate estimation model for repair and maintenance of bridges in developing countries using artificial neural networks. Cost and design data for two categories of repair bridges were used for training and testing our neural network model, with only three main parameters used in estimating the total cost of repairing bridges. An accuracy of 96% was achieved.