Volume 11 Issue 4
Sep.  2020
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Wengang Zhang, Runhong Zhang, Chongzhi Wu, Anthony Teck Chee Goh, Suzanne Lacasse, Zhongqiang Liu, Hanlong Liu. State-of-the-art review of soft computing applications inunderground excavations[J]. Geoscience Frontiers, 2020, (4): 1095-1106. doi: 10.1016/j.gsf.2019.12.003
Citation: Wengang Zhang, Runhong Zhang, Chongzhi Wu, Anthony Teck Chee Goh, Suzanne Lacasse, Zhongqiang Liu, Hanlong Liu. State-of-the-art review of soft computing applications in underground excavations[J]. Geoscience Frontiers, 2020, (4): 1095-1106. doi: 10.1016/j.gsf.2019.12.003

State-of-the-art review of soft computing applications in underground excavations

doi: 10.1016/j.gsf.2019.12.003

The authors acknowledge the invitation for this review article from Geoscience Frontiers. They are also grateful to the authors of papers referred, as well as the suggestive comments from the two reviewers. This work was supported by High-end Foreign Expert Introduction program (No. G20190022002) and Chongqing Construction Science and Technology Plan Project (2019–0045). The financial support is gratefully acknowledged.

  • Received Date: 2019-09-25
  • Rev Recd Date: 2019-11-19
  • Publish Date: 2020-09-07
  • Soft computing techniques are becoming even more popular and particularly amenable to model the complex behaviors of most geotechnical engineering systems since they have demonstrated superior predictive capacity, compared to the traditional methods. This paper presents an overview of some soft computing techniques as well as their applications in underground excavations. A case study is adopted to compare the predictive performances of soft computing techniques including eXtreme Gradient Boosting (XGBoost), Multivariate Adaptive Regression Splines (MARS), Artificial Neural Networks (ANN), and Support Vector Machine (SVM) in estimating the maximum lateral wall deflection induced by braced excavation. This study also discusses the merits and the limitations of some soft computing techniques, compared with the conventional approaches available.
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