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Vol.2 , No. 5, Publication Date: Sep. 26, 2017, Page: 57-66
 pavement specimens with the different contents of the added rice husk ash (RHA) as a supplementary material are presented. The obtained results from the proposed RBF and ANN models are compared with each other and with the experimental data, which show a good agreement between the predicted values and the experimental data. The proposed ANN model is more accurate and reliable than the proposed RBF model. According to the results of this study, the optimal content for increasing of the compressive strength and reducing of permeability was obtained by substituting 9% and 11% of the cement by RHAin gyration number 70, respectively. However, adding a little more than 11% RHA reduced the compressive strength.&picture=http://www.aascit.org/aascit/decorators/img/journal/816.jpg)
| [1] | Ebrahim Khalilzadeh Vahidi, Department of Civil Engineering, Razi University, Kermanshah, Iran. |
| [2] | Maryam Mokhtari Malekabadi, Department of Civil Engineering, Razi University, Kermanshah, Iran. |
| [3] | Mohammad Mahdi Roshani, Department of Young Researchers and Elite, Islamic Azad University, Kermanshah, Iran. |
| [4] | Gholam Hossein Roshani, Department of Electrical Engineering, University of Technology, Kermanshah, Iran. |
| [5] | Abbas Rezaei, Department of Electrical Engineering, University of Technology, Kermanshah, Iran. |
An ANN is a system based on the operation of biological neural networks. ANNs have been used in many different applications such as control, electronics, and communications. In this paper, the accurate models based on ANN and RBF in order to predict the permeability and compressive strength in the roller compacted concrete (RCC) pavement specimens with the different contents of the added rice husk ash (RHA) as a supplementary material are presented. The obtained results from the proposed RBF and ANN models are compared with each other and with the experimental data, which show a good agreement between the predicted values and the experimental data. The proposed ANN model is more accurate and reliable than the proposed RBF model. According to the results of this study, the optimal content for increasing of the compressive strength and reducing of permeability was obtained by substituting 9% and 11% of the cement by RHAin gyration number 70, respectively. However, adding a little more than 11% RHA reduced the compressive strength.
Keywords
Radial Basis Function, Modeling, RHA, RCC Pavement, Servopac Gyratory Compactor
Reference
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