SPR-4714: Use of Machine Learning Methods to Obtain a Reliable Predictive Model for Resilient Modulus of Subgrade Soil
| 项目名称： | SPR-4714: Use of Machine Learning Methods to Obtain a Reliable Predictive Model for Resilient Modulus of Subgrade Soil |
| 摘要： | This research will use machine learning to develop/train data model(s) for predicting the resilient modulus of soil in the state of Indiana. The developed model(s) will reduce the need for routine iterative laboratory testing conducted for obtaining the resilient modulus of soil, which is complicated, resource intensive, time consuming, and expensive. In addition, based on the developed model(s), recommendations will be provided for future sampling locations. |
| 状态： | Active |
| 资金： | 63841 |
| 资助组织： | Purdue University/Indiana Department of Transportation JHRP |
| 主要研究人员： | Khoshnevisan, Sara；Norouzi, Mehdi |
| 开始时间： | 20221001 |
| 预计完成日期： | 20240331 |
| 主题领域： | Geotechnology；Highways |
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