Please use this identifier to cite or link to this item:
http://repository.futminna.edu.ng:8080/jspui/handle/123456789/15123| Title: | Application of Artificial Neural Network in Predicting Compressive Strength of Vege Block |
| Authors: | ABDULRAHMAN, HASSAN SHUAIBU JOHNSON, O A MADZLAN, N. KAMARUDDIN, I OLORUNTOBI, O.O. |
| Keywords: | Artificial neural network, compressive strength, linear regression, waste cooking oil |
| Issue Date: | 5-Jan-2016 |
| Publisher: | Maxwell Scientific Publication Corp. |
| Abstract: | Vege block is a building or construction block manufactured from the mixture of sand aggregates and waste cooking oil as a sustainable binder. This study explores the use of Artificial Neural Network (ANN) in the prediction of the compressive strength. Nine ANN models were developed with different hidden neurons ranges from 7-15 and it performances were tested after properly trained using the Root Mean Square Error (RMSE) and coefficient of determination(R-square) and correlation coefficient (r). The result shows that model with 8 hidden neurons show a better performance. |
| URI: | http://repository.futminna.edu.ng:8080/jspui/handle/123456789/15123 |
| Appears in Collections: | Civil Engineering |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Application_of_Artificial_Neural_Network_Published.pdf | 334.06 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.