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

Autor:	Mohamed Bouabaz, Mounir Hamami
Rok vydání:	2008
Předmět:	Engineering Multidisciplinary Cost estimate Artificial neural network Design data Total cost business.industry Accurate estimation Artificial intelligence Machine learning computer.software_genre business computer
Zdroj:	American Journal of Applied Sciences. 5:334-339
ISSN:	1546-9239
DOI:	10.3844/ajassp.2008.334.339
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8eb325af4ec0c2eaa9cfe29df7d60ad8 https://doi.org/10.3844/ajassp.2008.334.339 Zobrazit plný text záznamu