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dc.contributor.authorMishra M.en_US
dc.contributor.authorRamana G.V.en_US
dc.contributor.authorMaity D.en_US
dc.date.accessioned2020-01-16T06:32:04Z-
dc.date.available2020-01-16T06:32:04Z-
dc.date.issued2020-
dc.identifier.urihttp://dx.doi.org/10.1007/s10706-019-01037-2-
dc.identifier.urihttp://idr.iitbbs.ac.in/jspui/handle/2008/2528-
dc.description.abstractIn 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.en_US
dc.language.isoenen_US
dc.subjectArtificial intelligenceen_US
dc.subjectMultiverse optimiseren_US
dc.subjectNoncircular slip surfaceen_US
dc.subjectSlope stabilityen_US
dc.subjectUncertaintyen_US
dc.titleMultiverse Optimisation Algorithm for Capturing the Critical Slip Surface in Slope Stability Analysisen_US
dc.typeArticleen_US
Appears in Collections:Research Publications

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