Numerical ANFIS-based formulation for prediction of the ultimate axial load bearing capacity of piles through CPT data

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Ghorbani, Behnam ORCID: 0000-0002-8651-4402, Sadrossadat, Ehsan ORCID: 0000-0002-7110-4363, Bolouri Bazaz, Jafar and Rahimzadeh Oskooei, Parisa (2018) Numerical ANFIS-based formulation for prediction of the ultimate axial load bearing capacity of piles through CPT data. Geotechnical and Geological Engineering, 36. pp. 2057-2076. ISSN 0960-3182

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/45168
DOI 10.1007/s10706-018-0445-7
Official URL https://link.springer.com/article/10.1007/s10706-0...
Subjects Current > FOR (2020) Classification > 4602 Artificial intelligence
Current > Division/Research > Institute for Sustainable Industries and Liveable Cities
Keywords neuro fuzzy interference systems, ANFIS, load bearing capacity, cone penetration testing, CPT
Citations in Scopus 36 - View on Scopus
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