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Tytuł:
Development of cost estimation models based on ANN ensembles and the SVM method
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Temat i słowa kluczowe:
construction cost estimation ; cost modelling ; ensemble of neural networks ; support vector machines ; koszty budowy ; modelowanie kosztów ; zespół sieci neuronowych
Abstract:
Cost estimation, as one of the key processes in construction projects, provides the basis for a number of project-related decisions. This paper presents some results of studies on the application of artificial intelligence and machine learning in cost estimation. The research developed three original models based either on ensembles of neural networks or on support vector machines for the cost prediction of the floor structural frames of buildings. ; According to the criteria of general metrics (RMSE, MAPE), the three models demonstrate similar predictive performance. MAPE values computed for the training and testing of the three developed models range between 5% and 6%. The accuracy of cost predictions given by the three developed models is acceptable for the cost estimates of the floor structural frames of buildings in the early design stage of the construction project. Analysis of error distribution revealed a degree of superiority for the model based on support vector machines.
Opis:
tytuł dodatkowy: Prace z Inżynierii Lądowej i Środowiska
Wydawca:
Zielona Góra: Oficyna Wydawnicza Uniwersytetu Zielonogórskiego
Data wydania:
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DOI:
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Źródło:
Civil and Environmental Engineering Reports (CEER), no 30, vol. 3