ANN based Performance Evaluation of Fiber Reinforced Concrete Beams Incorporating Nano Fillers and Micro Fillers
Fuente:
Zenodo
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Recurso digital |
| Veröffentlicht: |
Zenodo
2022
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866901104884711424 |
|---|---|
| author | K. Meenatchi P. N. Raghunath K. Suguna |
| author_facet | K. Meenatchi P. N. Raghunath K. Suguna |
| contents | An attempt has been made in this study to evaluate the performance of fiber reinforced concrete beams incorporating nano fillers and micro fillers using the neural computational tool ANN. The test data necessary for this exercise were collected from published literature. MATLAB software has been used for this purpose. Back propagation network with Levenberg Marquardt Algorithm, Bayesian Regularization Algorithm and Scaled Conjugate Gradient Algorithm was chosen for the proposed study .The length, breadth, depth, Ast, Asv, fck and fy were considered as input parameters and first crack load, deflection at first crack load, yield load, deflection at yield load, ultimate load and deflection at ultimate load were considered as target parameters. In the present study comparison has been made between the test results from published literature and results predicted from ANN using different algorithms. Statistical indicators such as RMSE, R² and MAPE were found to estimate the accuracy of results predicted through ANN modeling. The results predicted through ANN modeling exhibit better convergence with the experimental results collected through published literature. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18447082 |
| institution | Zenodo |
| language | |
| publishDate | 2022 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | ANN based Performance Evaluation of Fiber Reinforced Concrete Beams Incorporating Nano Fillers and Micro Fillers K. Meenatchi P. N. Raghunath K. Suguna ANN Deflection Fiber Reinforced Concrete MATLAB. An attempt has been made in this study to evaluate the performance of fiber reinforced concrete beams incorporating nano fillers and micro fillers using the neural computational tool ANN. The test data necessary for this exercise were collected from published literature. MATLAB software has been used for this purpose. Back propagation network with Levenberg Marquardt Algorithm, Bayesian Regularization Algorithm and Scaled Conjugate Gradient Algorithm was chosen for the proposed study .The length, breadth, depth, Ast, Asv, fck and fy were considered as input parameters and first crack load, deflection at first crack load, yield load, deflection at yield load, ultimate load and deflection at ultimate load were considered as target parameters. In the present study comparison has been made between the test results from published literature and results predicted from ANN using different algorithms. Statistical indicators such as RMSE, R² and MAPE were found to estimate the accuracy of results predicted through ANN modeling. The results predicted through ANN modeling exhibit better convergence with the experimental results collected through published literature. |
| title | ANN based Performance Evaluation of Fiber Reinforced Concrete Beams Incorporating Nano Fillers and Micro Fillers |
| topic | ANN Deflection Fiber Reinforced Concrete MATLAB. |
| url | https://doi.org/10.5281/zenodo.18447082 |