Determination of stability of slope using Minimax Probability Machine
Determination of stability of slope using Minimax Probability Machine
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DOI：
10.1080/17499518.2014.897488
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发表时间：
2014-03
期刊：
影响因子：
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通讯作者：
P. Samui;R. Hariharan;Jayaraman Karthikeyan
中科院分区：
文献类型：
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作者：
P. Samui;R. Hariharan;Jayaraman Karthikeyan
本文检验了极小极大概率机 (MPM) 确定边坡稳定性的能力。 MPM 是在概率框架内构建的。本研究使用 MPM 作为分类和回归工具。单位重量 (γ)、内聚力 (c)、内摩擦角 (φ)、坡度角 (β)、高度 (H) 和孔隙水压力系数 (ru) 已用作 MPM 模型的输入。 MPM 的输出是边坡的稳定状态和安全系数（F）。 MPM 的结果与人工神经网络模型进行了比较。实验结果表明，所开发的 MPM 是一种很有前途的边坡稳定性测定工具。
This article examines the capability of Minimax Probability Machine (MPM) for the determination of stability of slope. MPM is constructed within a probabilistic framework. This study uses MPM as classification and regression tools. Unit weight (γ), cohesion (c), angle of internal friction (φ), slope angle (β), height (H) and pore water pressure coefficient (ru) have been used as inputs of the MPM model. The outputs of MPM are stability status of slope and factor of safety (F). The results of MPM have been compared with the artificial neural network models. The experimental results demonstrate that the developed MPM is a promising tool for the determination of stability of slope.