Application of Artificial Intelligence for the Estimation of Concrete and Reinforcement Consumption in the Construction of Integral Bridges
Estimation of basic material consumption in civil engineering is very important in the initial phases of project implementation. Its importance is reflected in the impact of material quantities on forming the prices of individual positions, hence on forming the total cost of construction. The constr...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2020/8645031 |
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| author | Željka Beljkaš Miloš Knežević Snežana Rutešić Nenad Ivanišević |
| author_facet | Željka Beljkaš Miloš Knežević Snežana Rutešić Nenad Ivanišević |
| author_sort | Željka Beljkaš |
| collection | DOAJ |
| description | Estimation of basic material consumption in civil engineering is very important in the initial phases of project implementation. Its importance is reflected in the impact of material quantities on forming the prices of individual positions, hence on forming the total cost of construction. The construction companies use the estimate of material quantity, among other things, as a base to make a bid on the market. The precision of the offer, taking into account the overall conditions of the business realization, directly influences the profit that the company can make on a specific project. In the early stages of project implementation, there are not enough available data, especially when it comes to the data needed to estimate material consumption, and therefore, the accuracy of material consumption estimation in the early stages of project realization is smaller. The paper presents the research on the use of artificial intelligence for the estimation of concrete and reinforcement consumption and the selection of optimal models for estimation. The estimation model was developed by using artificial neural networks. The best artificial neural network model showed high accuracy in material consumption estimation expressed as the mean absolute percentage error, 8.56% for concrete consumption estimate and 17.31% for reinforcement consumption estimate. |
| format | Article |
| id | doaj-art-8defa210b03641ae93d427f970eec3bb |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-8defa210b03641ae93d427f970eec3bb2025-02-03T06:06:34ZengWileyAdvances in Civil Engineering1687-80861687-80942020-01-01202010.1155/2020/86450318645031Application of Artificial Intelligence for the Estimation of Concrete and Reinforcement Consumption in the Construction of Integral BridgesŽeljka Beljkaš0Miloš Knežević1Snežana Rutešić2Nenad Ivanišević3Faculty of Civil Engineering, University of Montenegro, Podgorica 81000, MontenegroFaculty of Civil Engineering, University of Montenegro, Podgorica 81000, MontenegroFaculty of Civil Engineering, University of Montenegro, Podgorica 81000, MontenegroFaculty of Civil Engineering, University in Belgrade, Belgrade 11120, SerbiaEstimation of basic material consumption in civil engineering is very important in the initial phases of project implementation. Its importance is reflected in the impact of material quantities on forming the prices of individual positions, hence on forming the total cost of construction. The construction companies use the estimate of material quantity, among other things, as a base to make a bid on the market. The precision of the offer, taking into account the overall conditions of the business realization, directly influences the profit that the company can make on a specific project. In the early stages of project implementation, there are not enough available data, especially when it comes to the data needed to estimate material consumption, and therefore, the accuracy of material consumption estimation in the early stages of project realization is smaller. The paper presents the research on the use of artificial intelligence for the estimation of concrete and reinforcement consumption and the selection of optimal models for estimation. The estimation model was developed by using artificial neural networks. The best artificial neural network model showed high accuracy in material consumption estimation expressed as the mean absolute percentage error, 8.56% for concrete consumption estimate and 17.31% for reinforcement consumption estimate.http://dx.doi.org/10.1155/2020/8645031 |
| spellingShingle | Željka Beljkaš Miloš Knežević Snežana Rutešić Nenad Ivanišević Application of Artificial Intelligence for the Estimation of Concrete and Reinforcement Consumption in the Construction of Integral Bridges Advances in Civil Engineering |
| title | Application of Artificial Intelligence for the Estimation of Concrete and Reinforcement Consumption in the Construction of Integral Bridges |
| title_full | Application of Artificial Intelligence for the Estimation of Concrete and Reinforcement Consumption in the Construction of Integral Bridges |
| title_fullStr | Application of Artificial Intelligence for the Estimation of Concrete and Reinforcement Consumption in the Construction of Integral Bridges |
| title_full_unstemmed | Application of Artificial Intelligence for the Estimation of Concrete and Reinforcement Consumption in the Construction of Integral Bridges |
| title_short | Application of Artificial Intelligence for the Estimation of Concrete and Reinforcement Consumption in the Construction of Integral Bridges |
| title_sort | application of artificial intelligence for the estimation of concrete and reinforcement consumption in the construction of integral bridges |
| url | http://dx.doi.org/10.1155/2020/8645031 |
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