Prediction of Safe Bearing Capacity of Noncohesive Soil in Arid Zone Using Artificial Neural Networks-Reference-Cited by-同舟云学术

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Prediction of Safe Bearing Capacity of Noncohesive Soil in Arid Zone Using Artificial Neural Networks

Published:2016-04 Issue:2 Volume:16 Page:04015044
ISSN:1532-3641
Container-title:International Journal of Geomechanics
language:en
Short-container-title:Int. J. Geomech.

Author:

Gupta Rajiv¹,Goyal Kartik²,Yadav Navneet²

Affiliation:

1. Senior Professor, Dept. of Civil Engineering, Birla Institute of Technology and Science, Pilani, Rajasthan 333031, India (corresponding author).

2. Student, Dept. of Civil Engineering, Birla Institute of Technology and Science, Pilani, Rajasthan 333031, India.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Soil Science

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29GM.1943-5622.0000514

Reference46 articles.

1. Load-displacement and bearing capacity of foundations on granular soils using a multi-surface kinematic constitutive soil model

2. Numerical evaluation of the bearing capacity factor of ring footings

3. Experimental and numerical investigation of the bearing capacity of model circular and ring footings on reinforced sand

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