补给线 发表于 2025-3-21 19:06:03
书目名称Soil Dynamics, Earthquake and Computational Geotechnical Engineering影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0871228<br><br> <br><br>书目名称Soil Dynamics, Earthquake and Computational Geotechnical Engineering影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0871228<br><br> <br><br>书目名称Soil Dynamics, Earthquake and Computational Geotechnical Engineering网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0871228<br><br> <br><br>书目名称Soil Dynamics, Earthquake and Computational Geotechnical Engineering网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0871228<br><br> <br><br>书目名称Soil Dynamics, Earthquake and Computational Geotechnical Engineering被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0871228<br><br> <br><br>书目名称Soil Dynamics, Earthquake and Computational Geotechnical Engineering被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0871228<br><br> <br><br>书目名称Soil Dynamics, Earthquake and Computational Geotechnical Engineering年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0871228<br><br> <br><br>书目名称Soil Dynamics, Earthquake and Computational Geotechnical Engineering年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0871228<br><br> <br><br>书目名称Soil Dynamics, Earthquake and Computational Geotechnical Engineering读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0871228<br><br> <br><br>书目名称Soil Dynamics, Earthquake and Computational Geotechnical Engineering读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0871228<br><br> <br><br>COLON 发表于 2025-3-22 00:08:13
Potential Use of Fine Fraction of Municipal Solid Waste as Replacement of Soil in Embankment,mana, Varanasi) from where the MSW sample was collected. The numerical modelling of the embankment predicts the settlement and stability of the road embankment under traffic loads, which were found to be within the permissible limits. Although this is just a preliminary study, an extensive exercise is required to check its suitability.Delirium 发表于 2025-3-22 02:56:06
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Evaluation of Compactive Parameters of Soil Using Machine Learning,. Artificial intelligence has two subsets; one is machine learning, and the second is deep learning. In this technical article, the regression analysis, multilayer perceptron class-based neural network models are employed to predict the compactive parameters (optimum moisture content and maximum dryTartar 发表于 2025-3-23 02:24:08
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