Application of Artificial Neural Networks for Predicting the Bearing Capacity of Shallow Foundations on Rock Masses
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
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1434-453X
- Extent
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Online-Ressource
- Language
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Englisch
- Notes
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online resource.
- Bibliographic citation
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Application of Artificial Neural Networks for Predicting the Bearing Capacity of Shallow Foundations on Rock Masses ; volume:54 ; number:9 ; day:29 ; month:6 ; year:2021 ; pages:5071-5094 ; date:9.2021
Rock mechanics and rock engineering ; 54, Heft 9 (29.6.2021), 5071-5094, 9.2021
- Creator
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Millán, M. A.
Galindo, R.
Alencar, A.
- Contributor
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SpringerLink (Online service)
- DOI
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10.1007/s00603-021-02549-1
- URN
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urn:nbn:de:101:1-2021111221321449870286
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:37 AM CEST
Data provider
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Associated
- Millán, M. A.
- Galindo, R.
- Alencar, A.
- SpringerLink (Online service)
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Influence of the groundwater level on the bearing capacity of shallow foundations on the rock mass
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Bearing capacity of shallow foundations: a focus on the depth factors in combination with the respective N-factors
Geogrid reinforcement for improving bearing capacity and stability of square foundations
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Development of Z number-based fuzzy inference system to predict bearing capacity of circular foundations
Predicting axial-bearing capacity of fully grouted rock bolting systems by applying an ensemble system
Load capacity of shallow embedded anchor channels
Integrated machine learning for modeling bearing capacity of shallow foundations
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Simulation of settlement and bearing capacity of shallow foundations with soft particle code (SPARC) and FE
The Effect of Loading Inclination and Eccentricity on the Bearing Capacity of Shallow Foundations: A Review
Influence of the groundwater level on the bearing capacity of shallow foundations on the rock mass
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Bearing capacity of shallow foundations: a focus on the depth factors in combination with the respective N-factors
Geogrid reinforcement for improving bearing capacity and stability of square foundations
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Development of Z number-based fuzzy inference system to predict bearing capacity of circular foundations
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