Skip to the main content

Preliminary communication

https://doi.org/10.14256/JCE.2273.2017

Estimation of recycling capacity using ANN and SVM

Aleksandra Vujkov
Dragana Bibić
Igor Peško
Vladimir Mučenski
Jasmina Dražić
Milan Trivunić


Full text: croatian pdf 203 Kb

page 783-792

downloads: 201

cite

Full text: english pdf 201 Kb

page 783-792

downloads: 156

cite


Abstract

This paper presents estimation of the quantity of concrete and reinforcement that can be recycled for residential buildings constructed as skeleton structures. Models based on artificial intelligence, involving the use of Artificial Neural Networks (ANNs) and the Support Vector Machines (SVM) methods, were formed in order to estimate quantities of these materials. The results show that the application of ANNs and SVM methods is a good solution for the estimation of recycling capacity. The mean absolute percentage error (MAPE) for the selected ANNs for predicting quantity of concrete and reinforcement is 8.74 % and 12.58 %, respectively.

Keywords

buildings; recycling; concrete; reinforcement; artificial neural networks; support vector machine method

Hrčak ID:

207200

URI

https://hrcak.srce.hr/207200

Publication date:

23.10.2018.

Article data in other languages: croatian

Visits: 1.038 *