Estimation Of The Unitary Cost Of The Square Meter Popular Housing In The City Of Manaus Based On The Most Important Inputs, Using Artificial Neural Networks

Abstract

Civil construction is one of the most expressive sectors in the economy, development, and employability in Brazil. One of the main challenges in the construction of low-income housing is the lack of predictability of costs during project execution. This study developed a tool based on Artificial Neural Networks (ANN), using data from the CUB and INCC construction price databases to predict the cost per square meter of social housing in Manaus. The tool showed a high correlation between the databases, validating its reliability and applicability in cost estimation.