Application of MGGP in Predicting Bearing Capacity of a Strip Footing Resting on the Crest of a Marginal Soil Hillslope

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@Article{Acharyya:2024:KJCE,

• author = "Rana Acharyya and Arindam Dey",
• title = "Application of {MGGP} in Predicting Bearing Capacity of a Strip Footing Resting on the Crest of a Marginal Soil Hillslope",
• journal = "KSCE Journal of Civil Engineering",
• year = "2024",
• volume = "28",
• number = "10",
• pages = "4244--4257",
• keywords = "genetic algorithms, genetic programming, Strip footing on slope, Finite element analysis, Maximum bearing strength, MGGP, Sensitivity assessment",
• ISSN = "1226-7988",
• URL = "https://www.sciencedirect.com/science/article/pii/S1226798825001114",
• DOI = "doi:10.1007/s12205-024-1217-y",
• abstract = "A set of finite element investigations are performed to examine the maximum bearing strength of strip footings positioned on the crest of a cohesive-frictional marginal soil hillslope. In this regard, the influence of contributing geometrical and geotechnical parameters on the maximum bearing strength of the footing are illustrated. It is revealed that the nearness of slope face has negligible influence on the bearing strength of footing if it is located at a setback distance beyond six times the footing width. Further, using multi-gene genetic programming technique, a predictive relationship between the maximum bearing strength and the contributory factors is established and validated through relevant experimental findings. The hyper-parameters of the MGGP model are suitably optimised, as indicated by the coefficient of correlation attaining high magnitudes. A sensitivity analysis based on local perturbation is conducted to recognise the importance ranking of the contributory parameters. It is revealed that the friction angle of slope material predominantly influences the evaluation of maximum bearing strength for strip footing on slopes, followed by other contributing factors",

}

Genetic Programming entries for Rana Acharyya Arindam Dey

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