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Determination of Bearing Capacity of Shallow Foundation Using Soft Computing
Jagan J, Chowdhury S, Goyal P, Samui P, Dalkiliç Y.
Published in IGI Global
Pages: 1590 - 1626
The ultimate bearing capacity is an important criterion for the successful implementation of any geotechnical projects. This chapter studies the feasibility of employing Gaussian process regression (GPR), Extreme learning machine (ELM) and Minimax probability machine regression (MPMR) for prediction of ultimate bearing capacity of shallow foundation based on cohesionless soils. The developed models have been compared on the basis of coefficient of relation (R) values (GPR= 0.9625, ELM= 0.938, MPMR= 0.9625). The results show that MPMR is more efficient tool but the models of GPR and ELM also gives satisfactory results.
About the journal
JournalNature-Inspired Computing
PublisherIGI Global
Open Access0