Cost Forecasting of Public Construction Projects Using Multilayer Perceptron Artificial Neural Networks: A Case Study
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| Natura: | Artículo científico |
| Lingua: | en |
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Universidad Nacional de Colombia
2021
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| _version_ | 1876460900117905408 |
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| author | Alcineide Pessoa |
| author_facet | Alcineide Pessoa |
| contents | Cost Forecasting of Public Construction Projects Using Multilayer Perceptron Artificial Neural Networks: A Case Study Alcineide Pessoa Gean Sousa Luiz Maurício Furtado Maués Felipe Campos Alvarenga Débora de Gois Santos Ingeniería costs Public undertakings artificial neural network The execution of public sector construction projects often requires the use of financial resources not foreseen during the tendering phase, which causes management problems. This study aims to present a computational model based on artificial intelligence, specifically on artificial neural networks, capable of forecasting the execution cost of construction projects for Brazilian educational public buildings. The database used in the training and testing of the neural model was obtained from the online system of the Ministry of Education. The neural network used was a multilayer perceptron as a backpropagation algorithm optimized through the gradient descent method. To evaluate the obtained results, the mean absolute percentage errors and the Pearson correlation coefficients were calculated. Some hypothesis tests were also carried out in order to verify the existence of significant differences between real values and those obtained by the neural network. The average percentage errors between predicted and actual values varied between 5% and 9%, and the correlation values reached 0,99. The results demonstrated that it is possible to use artificial intelligence as an auxiliary mechanism to plan construction projects, especially in the public sector. 2021 artículo científico 0120-5609 https://www.redalyc.org/articulo.oa?id=64379876007 https://www.redalyc.org/journal/643/64379876007/ https://www.redalyc.org/journal/643/64379876007/html/ https://www.redalyc.org/journal/643/64379876007/64379876007.epub https://www.redalyc.org/journal/643/64379876007/movil 10.15446/ing.investig.v41n3.87737 en http://www.redalyc.org/revista.oa?id=643 Ingeniería e Investigación application/pdf Universidad Nacional de Colombia Ingeniería e Investigación (Colombia) Num.3 Vol.41 |
| format | Artículo científico |
| id | redalyc_64379876007 |
| institution | Redalyc |
| language | en |
| publishDate | 2021 |
| publisher | Universidad Nacional de Colombia |
| spellingShingle | Cost Forecasting of Public Construction Projects Using Multilayer Perceptron Artificial Neural Networks: A Case Study Alcineide Pessoa Ingeniería costs Public undertakings artificial neural network Cost Forecasting of Public Construction Projects Using Multilayer Perceptron Artificial Neural Networks: A Case Study Alcineide Pessoa Gean Sousa Luiz Maurício Furtado Maués Felipe Campos Alvarenga Débora de Gois Santos Ingeniería costs Public undertakings artificial neural network The execution of public sector construction projects often requires the use of financial resources not foreseen during the tendering phase, which causes management problems. This study aims to present a computational model based on artificial intelligence, specifically on artificial neural networks, capable of forecasting the execution cost of construction projects for Brazilian educational public buildings. The database used in the training and testing of the neural model was obtained from the online system of the Ministry of Education. The neural network used was a multilayer perceptron as a backpropagation algorithm optimized through the gradient descent method. To evaluate the obtained results, the mean absolute percentage errors and the Pearson correlation coefficients were calculated. Some hypothesis tests were also carried out in order to verify the existence of significant differences between real values and those obtained by the neural network. The average percentage errors between predicted and actual values varied between 5% and 9%, and the correlation values reached 0,99. The results demonstrated that it is possible to use artificial intelligence as an auxiliary mechanism to plan construction projects, especially in the public sector. 2021 artículo científico 0120-5609 https://www.redalyc.org/articulo.oa?id=64379876007 https://www.redalyc.org/journal/643/64379876007/ https://www.redalyc.org/journal/643/64379876007/html/ https://www.redalyc.org/journal/643/64379876007/64379876007.epub https://www.redalyc.org/journal/643/64379876007/movil 10.15446/ing.investig.v41n3.87737 en http://www.redalyc.org/revista.oa?id=643 Ingeniería e Investigación application/pdf Universidad Nacional de Colombia Ingeniería e Investigación (Colombia) Num.3 Vol.41 |
| title | Cost Forecasting of Public Construction Projects Using Multilayer Perceptron Artificial Neural Networks: A Case Study |
| topic | Ingeniería costs Public undertakings artificial neural network |
| url | https://www.redalyc.org/articulo.oa?id=64379876007 https://www.redalyc.org/journal/643/64379876007/ https://www.redalyc.org/journal/643/64379876007/html/ https://www.redalyc.org/journal/643/64379876007/64379876007.epub https://www.redalyc.org/journal/643/64379876007/movil |