Pile-Raft Settlements Prediction under Coupled Static-Dynamic Loads Using Four Heuristic Regression Approaches
One of the main driving factors for structures’ evaluation is the foundation settlement. Measuring structures’ settlement in field is costly especially when heavy loads are applied. Settlement prediction models can be used to avoid the high cost of settlement field tests. Four advanced heuristic reg...
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2018/3425461 |
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| author | Mosbeh R. Kaloop Jong Wan Hu Emad Elbeltagi |
| author_facet | Mosbeh R. Kaloop Jong Wan Hu Emad Elbeltagi |
| author_sort | Mosbeh R. Kaloop |
| collection | DOAJ |
| description | One of the main driving factors for structures’ evaluation is the foundation settlement. Measuring structures’ settlement in field is costly especially when heavy loads are applied. Settlement prediction models can be used to avoid the high cost of settlement field tests. Four advanced heuristic regression methods are developed and applied in this study to estimate raft foundations’ settlement, namely, multivariate adaptive regression splines (MARS), M5 model tree (M5Tree), generalized regression neural networks (GRNN), and support vector regression (SVR) techniques. Simulation of raft pile foundations is utilized to calculate the settlements of piles under the effect of static and dynamic loads. Previous studies are compared with the newly developed models. The results show that the four models can be used to accurately predict foundations’ settlements in the training stage. Also, the results reveal that the MARS and SVR models performed slightly better than the M5Tree and GRNN models in the testing stage and accordingly can be used to predict foundations’ settlement. The SVR model outperformed other models when few numbers of measurements are available. |
| format | Article |
| id | doaj-art-4adae3a63ea6403195613e7f6a146851 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-4adae3a63ea6403195613e7f6a1468512025-02-03T05:48:20ZengWileyShock and Vibration1070-96221875-92032018-01-01201810.1155/2018/34254613425461Pile-Raft Settlements Prediction under Coupled Static-Dynamic Loads Using Four Heuristic Regression ApproachesMosbeh R. Kaloop0Jong Wan Hu1Emad Elbeltagi2Department of Civil and Environmental Engineering, Incheon National University, Incheon 22012, Republic of KoreaDepartment of Civil and Environmental Engineering, Incheon National University, Incheon 22012, Republic of KoreaDepartment of Structural Engineering, Mansoura University, Mansoura 35516, EgyptOne of the main driving factors for structures’ evaluation is the foundation settlement. Measuring structures’ settlement in field is costly especially when heavy loads are applied. Settlement prediction models can be used to avoid the high cost of settlement field tests. Four advanced heuristic regression methods are developed and applied in this study to estimate raft foundations’ settlement, namely, multivariate adaptive regression splines (MARS), M5 model tree (M5Tree), generalized regression neural networks (GRNN), and support vector regression (SVR) techniques. Simulation of raft pile foundations is utilized to calculate the settlements of piles under the effect of static and dynamic loads. Previous studies are compared with the newly developed models. The results show that the four models can be used to accurately predict foundations’ settlements in the training stage. Also, the results reveal that the MARS and SVR models performed slightly better than the M5Tree and GRNN models in the testing stage and accordingly can be used to predict foundations’ settlement. The SVR model outperformed other models when few numbers of measurements are available.http://dx.doi.org/10.1155/2018/3425461 |
| spellingShingle | Mosbeh R. Kaloop Jong Wan Hu Emad Elbeltagi Pile-Raft Settlements Prediction under Coupled Static-Dynamic Loads Using Four Heuristic Regression Approaches Shock and Vibration |
| title | Pile-Raft Settlements Prediction under Coupled Static-Dynamic Loads Using Four Heuristic Regression Approaches |
| title_full | Pile-Raft Settlements Prediction under Coupled Static-Dynamic Loads Using Four Heuristic Regression Approaches |
| title_fullStr | Pile-Raft Settlements Prediction under Coupled Static-Dynamic Loads Using Four Heuristic Regression Approaches |
| title_full_unstemmed | Pile-Raft Settlements Prediction under Coupled Static-Dynamic Loads Using Four Heuristic Regression Approaches |
| title_short | Pile-Raft Settlements Prediction under Coupled Static-Dynamic Loads Using Four Heuristic Regression Approaches |
| title_sort | pile raft settlements prediction under coupled static dynamic loads using four heuristic regression approaches |
| url | http://dx.doi.org/10.1155/2018/3425461 |
| work_keys_str_mv | AT mosbehrkaloop pileraftsettlementspredictionundercoupledstaticdynamicloadsusingfourheuristicregressionapproaches AT jongwanhu pileraftsettlementspredictionundercoupledstaticdynamicloadsusingfourheuristicregressionapproaches AT emadelbeltagi pileraftsettlementspredictionundercoupledstaticdynamicloadsusingfourheuristicregressionapproaches |