Please use this identifier to cite or link to this item: http://idr.iitbbs.ac.in/jspui/handle/2008/2528
Title: Multiverse Optimisation Algorithm for Capturing the Critical Slip Surface in Slope Stability Analysis
Authors: Mishra M.
Ramana G.V.
Maity D.
Keywords: Artificial intelligence
Multiverse optimiser
Noncircular slip surface
Slope stability
Uncertainty
Issue Date: 2020
Abstract: In professional practice, slope stability assessment of natural or man-made slopes is performed using traditional limit-equilibrium-based methods. These methods often fail to identify the critical slip surface corresponding to the minimum factor of safety (FS). Optimisation methods based on stochastic search techniques can more easily locate the global optima solution than traditional methods can. The paper presents the application of the recently proposed multiverse optimisation (MVO) algorithm in determining the lowest FS along the critical slip surface. Four benchmark examples are analysed to test the performance of the multiverse optimiser for slope stability assessment. The results demonstrate that the MVO algorithm can capture the critical slip surface and compute its corresponding FS with a considerably low uncertainty. � 2019, Springer Nature Switzerland AG.
URI: http://dx.doi.org/10.1007/s10706-019-01037-2
http://idr.iitbbs.ac.in/jspui/handle/2008/2528
Appears in Collections:Research Publications

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