Use of an artificial neural network model for estimation of unfrozen water content in frozen soils
| العنوان: | Use of an artificial neural network model for estimation of unfrozen water content in frozen soils |
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| المؤلفون: | Jun-ping Ren, Xudong Fan, Xiong Yu, Sai Vanapalli, Shoulong Zhang |
| المصدر: | Canadian Geotechnical Journal. |
| بيانات النشر: | Canadian Science Publishing, 2023. |
| سنة النشر: | 2023 |
| مصطلحات موضوعية: | Geotechnical Engineering and Engineering Geology, Civil and Structural Engineering |
| الوصف: | The variation of unfrozen water content (UWC) has a significant influence on the physical and mechanical behaviors of frozen soils. Several empirical, semi-empirical, physical and theoretical models are available in the literature to estimate the UWC in frozen soils. However, these models have limitations due to the complex interactions of various influencing factors that are not well understood or fully established. For this reason, in the present study, an artificial neural network (ANN) modeling framework is proposed and the PyTorch package is used for predicting UWC. Extensive UWC data of various types of soils tested under various conditions were collected through an extensive search of the literature. The developed ANN model showed good performance for the testing dataset. Its performance was further compared with two traditional statistical models on four soils and found to outperform these traditional models. Detailed discussions on the developed ANN model, and its strengths and limitations in comparison to different other models are provided. The study demonstrates that the proposed ANN model is simple yet reliable for estimating the UWC of various soils. In addition, the summarized UWC data and the proposed machine learning modeling framework are valuable for future studies related to frozen soils. |
| تدمد: | 1208-6010 0008-3674 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::25b86691ae59349250f4012d39d45096 https://doi.org/10.1139/cgj-2022-0035 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi...........25b86691ae59349250f4012d39d45096 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 12086010 00083674 |
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