基于 CPT 的土的地震液化势建模的统一分类模型
A unified classification model for modeling of seismic liquefaction potential of soil based on CPT.
机构信息
Centre for Disaster Mitigation and Management, VIT University, Vellore 632014, India.
Annai Mira College of Engineering and Technology, Department of Computer Science, Arapakam, Vellore 632517, India.
出版信息
J Adv Res. 2015 Jul;6(4):587-92. doi: 10.1016/j.jare.2014.02.002. Epub 2014 Feb 14.
The evaluation of liquefaction potential of soil due to an earthquake is an important step in geosciences. This article examines the capability of Minimax Probability Machine (MPM) for the prediction of seismic liquefaction potential of soil based on the Cone Penetration Test (CPT) data. The dataset has been taken from Chi-Chi earthquake. MPM is developed based on the use of hyperplanes. It has been adopted as a classification tool. This article uses two models (MODEL I and MODEL II). MODEL I employs Cone Resistance (q c) and Cyclic Stress Ratio (CSR) as input variables. q c and Peak Ground Acceleration (PGA) have been taken as inputs for MODEL II. The developed MPM gives 100% accuracy. The results show that the developed MPM can predict liquefaction potential of soil based on q c and PGA.
基于圆锥贯入试验 (CPT) 数据，利用最小最大概率机 (MPM) 预测地震土液化势是地球科学中的一个重要步骤。本文探讨了最小最大概率机 (MPM) 在基于 CPT 数据预测地震土液化势方面的能力。该数据集取自集集地震。MPM 是基于超平面的使用而开发的。它已被用作分类工具。本文使用了两个模型 (模型 I 和模型 II)。模型 I 将圆锥阻力 (qc) 和循环应力比 (CSR) 作为输入变量。模型 II 将 qc 和峰值地面加速度 (PGA) 作为输入。所开发的 MPM 给出了 100%的准确率。结果表明，所开发的 MPM 可以基于 qc 和 PGA 预测土的液化势。
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