ELM-based adaptive neuro swarm intelligence techniques for predicting the California bearing ratio of soils in soaked conditions-Reference-Cited by-同舟云学术

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ELM-based adaptive neuro swarm intelligence techniques for predicting the California bearing ratio of soils in soaked conditions

Published:2021-10 Issue: Volume:110 Page:107595
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Bardhan Abidhan,Samui Pijush,Ghosh Kuntal^ORCID,Gandomi Amir H.,Bhattacharyya Siddhartha^ORCID

Publisher

Elsevier BV

Subject

Software

Reference88 articles.

1. The prediction of the california bearing ratio;Stephens;Civ. Eng. Siviele Ingenieurswese.,1990

2. Estimation of California bearing ratio by using soft computing systems;Yildirim;Expert Syst. Appl.,2011

3. Prediction of California bearing ratio (CBR) of fine grained soils by AI methods;Taskiran;Adv. Eng. Softw.,2010

4. A method of estiml4ting the california bearing ratio of cohesive soils from plasticity data *;Black,1943

5. The engineering characteristics of the lateritic gravels of Ghana;J.W.S.,1969

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