Evaluation of Ground Displacements Caused by Installing Jet Grouted Columns Using Machine Learning Methods
During the jet grouting process, large volumes of high pressurized fluids injected into the soils will cause significant ground displacements, which may bring harmful impacts on surrounding environment. Therefore, it is essential to provide an accurate estimation of the ground displacement in the de...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Advances in Civil Engineering |
| Online Access: | http://dx.doi.org/10.1155/2020/8857293 |
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| author | Zhi-Feng Wang Xing-Bin Peng Yong Liu Wen-Chieh Cheng Ya-Qiong Wang Chao-Jun Wu |
| author_facet | Zhi-Feng Wang Xing-Bin Peng Yong Liu Wen-Chieh Cheng Ya-Qiong Wang Chao-Jun Wu |
| author_sort | Zhi-Feng Wang |
| collection | DOAJ |
| description | During the jet grouting process, large volumes of high pressurized fluids injected into the soils will cause significant ground displacements, which may bring harmful impacts on surrounding environment. Therefore, it is essential to provide an accurate estimation of the ground displacement in the design stage. Based on multiple nonlinear regression (MNLR) and support vector regression (SVR), the prediction approaches are established, respectively. The column radius (Rc), Young’s modulus (E), and distance from column center to target point (LOA) are selected as the input parameters, while the displacement of target point A at the radial direction (δA) is taken as the output parameter. Comparisons results on the prediction performance of ground displacements indicate that the MNLR-based approach has a better prediction effect. The design charts of the MNLR-based approach for predicting the ground displacement are created, which will be helpful for the practicing engineers to get a quick estimation. |
| format | Article |
| id | doaj-art-6dc08a3321f641f2aa1d9f0ff9724bc5 |
| institution | Kabale University |
| issn | 1687-8086 1687-8094 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Civil Engineering |
| spelling | doaj-art-6dc08a3321f641f2aa1d9f0ff9724bc52025-08-20T03:33:50ZengWileyAdvances in Civil Engineering1687-80861687-80942020-01-01202010.1155/2020/88572938857293Evaluation of Ground Displacements Caused by Installing Jet Grouted Columns Using Machine Learning MethodsZhi-Feng Wang0Xing-Bin Peng1Yong Liu2Wen-Chieh Cheng3Ya-Qiong Wang4Chao-Jun Wu5School of Highway, Chang’an University, Xi’an 710064, ChinaSchool of Highway, Chang’an University, Xi’an 710064, ChinaSchool of Highway, Chang’an University, Xi’an 710064, ChinaSchool of Civil Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, ChinaSchool of Highway, Chang’an University, Xi’an 710064, ChinaJinan Rail Transit Group Co. Ltd., Jinan 250101, ChinaDuring the jet grouting process, large volumes of high pressurized fluids injected into the soils will cause significant ground displacements, which may bring harmful impacts on surrounding environment. Therefore, it is essential to provide an accurate estimation of the ground displacement in the design stage. Based on multiple nonlinear regression (MNLR) and support vector regression (SVR), the prediction approaches are established, respectively. The column radius (Rc), Young’s modulus (E), and distance from column center to target point (LOA) are selected as the input parameters, while the displacement of target point A at the radial direction (δA) is taken as the output parameter. Comparisons results on the prediction performance of ground displacements indicate that the MNLR-based approach has a better prediction effect. The design charts of the MNLR-based approach for predicting the ground displacement are created, which will be helpful for the practicing engineers to get a quick estimation.http://dx.doi.org/10.1155/2020/8857293 |
| spellingShingle | Zhi-Feng Wang Xing-Bin Peng Yong Liu Wen-Chieh Cheng Ya-Qiong Wang Chao-Jun Wu Evaluation of Ground Displacements Caused by Installing Jet Grouted Columns Using Machine Learning Methods Advances in Civil Engineering |
| title | Evaluation of Ground Displacements Caused by Installing Jet Grouted Columns Using Machine Learning Methods |
| title_full | Evaluation of Ground Displacements Caused by Installing Jet Grouted Columns Using Machine Learning Methods |
| title_fullStr | Evaluation of Ground Displacements Caused by Installing Jet Grouted Columns Using Machine Learning Methods |
| title_full_unstemmed | Evaluation of Ground Displacements Caused by Installing Jet Grouted Columns Using Machine Learning Methods |
| title_short | Evaluation of Ground Displacements Caused by Installing Jet Grouted Columns Using Machine Learning Methods |
| title_sort | evaluation of ground displacements caused by installing jet grouted columns using machine learning methods |
| url | http://dx.doi.org/10.1155/2020/8857293 |
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