Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming
An effort has been made to develop concrete compressive strength prediction models with the help of two emerging data mining techniques, namely, Artificial Neural Networks (ANNs) and Genetic Programming (GP). The data for analysis and model development was collected at 28-, 56-, and 91-day curing pe...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-01-01
|
| Series: | Advances in Materials Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2016/7648467 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832554897840537600 |
|---|---|
| author | Palika Chopra Rajendra Kumar Sharma Maneek Kumar |
| author_facet | Palika Chopra Rajendra Kumar Sharma Maneek Kumar |
| author_sort | Palika Chopra |
| collection | DOAJ |
| description | An effort has been made to develop concrete compressive strength prediction models with the help of two emerging data mining techniques, namely, Artificial Neural Networks (ANNs) and Genetic Programming (GP). The data for analysis and model development was collected at 28-, 56-, and 91-day curing periods through experiments conducted in the laboratory under standard controlled conditions. The developed models have also been tested on in situ concrete data taken from literature. A comparison of the prediction results obtained using both the models is presented and it can be inferred that the ANN model with the training function Levenberg-Marquardt (LM) for the prediction of concrete compressive strength is the best prediction tool. |
| format | Article |
| id | doaj-art-320ad09935e04f13ba73f4a4e9c4e8cf |
| institution | Kabale University |
| issn | 1687-8434 1687-8442 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Materials Science and Engineering |
| spelling | doaj-art-320ad09935e04f13ba73f4a4e9c4e8cf2025-02-03T05:50:07ZengWileyAdvances in Materials Science and Engineering1687-84341687-84422016-01-01201610.1155/2016/76484677648467Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic ProgrammingPalika Chopra0Rajendra Kumar Sharma1Maneek Kumar2Department of Computer Science and Engineering, Thapar University, Patiala 147004, IndiaDepartment of Computer Science and Engineering, Thapar University, Patiala 147004, IndiaDepartment of Civil Engineering, Thapar University, Patiala 147004, IndiaAn effort has been made to develop concrete compressive strength prediction models with the help of two emerging data mining techniques, namely, Artificial Neural Networks (ANNs) and Genetic Programming (GP). The data for analysis and model development was collected at 28-, 56-, and 91-day curing periods through experiments conducted in the laboratory under standard controlled conditions. The developed models have also been tested on in situ concrete data taken from literature. A comparison of the prediction results obtained using both the models is presented and it can be inferred that the ANN model with the training function Levenberg-Marquardt (LM) for the prediction of concrete compressive strength is the best prediction tool.http://dx.doi.org/10.1155/2016/7648467 |
| spellingShingle | Palika Chopra Rajendra Kumar Sharma Maneek Kumar Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming Advances in Materials Science and Engineering |
| title | Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming |
| title_full | Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming |
| title_fullStr | Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming |
| title_full_unstemmed | Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming |
| title_short | Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming |
| title_sort | prediction of compressive strength of concrete using artificial neural network and genetic programming |
| url | http://dx.doi.org/10.1155/2016/7648467 |
| work_keys_str_mv | AT palikachopra predictionofcompressivestrengthofconcreteusingartificialneuralnetworkandgeneticprogramming AT rajendrakumarsharma predictionofcompressivestrengthofconcreteusingartificialneuralnetworkandgeneticprogramming AT maneekkumar predictionofcompressivestrengthofconcreteusingartificialneuralnetworkandgeneticprogramming |