Assessment of Cyclic Resistance Ratio (CRR) in Silty Sands Using Artificial Neural Networks

Journals Menu

Follow SCIRP

ISSN Print: 2164-3164
ISSN Online: 2164-3172
www.scirp.org/journal/ojce
E-mail: ojce@scirp.org

"Assessment of Cyclic Resistance Ratio (CRR) in Silty Sands Using Artificial Neural Networks"
written by Hassan Sharafi, Sahar Jalili,
published by Open Journal of Civil Engineering, Vol.4 No.3, 2014

has been cited by the following article(s):

[1]	Assessment of Liquefaction Potential Based on a Probabilistic Model and Performing Reliability Analysis with Evaluation the Relative Importance of Model Parameters …
	Journal of Structural and Construction …, 2021

[2]	ارزیابی پتانسیل وقوع روانگرایی برمبنای ارائه یک مدل احتمالاتی و انجام تحلیل‌های قابلیت‌اعتماد همراه با بررسی اهمیت نسبی عدم قطعیت پارامترهای مدل‎
	نشریه مهندسی سازه و ساخت, 2021

[3]	Analysis of potential liquefaction of sandy soils using effective confining pressure
	2020

[4]	Application of artificial intelligence techniques in prediction of cyclic resistance ratio (CRR) of clean sands
	2020

[5]	THE USE OF ARTIFICIAL NEURAL NETWORKS (ANNS) IN GEOTECHNICS
	2019

Follow SCIRP

[1]	A Review on Impacts and Mitigation of Liquefaction of Soil Around the Tunnels Journal of Failure Analysis and Prevention, 2023 DOI:10.1007/s11668-023-01759-9

[2]	Application of artificial intelligence techniques in prediction of cyclic resistance ratio (CRR) of clean sands IOP Conference Series: Earth and Environmental Science, 2020 DOI:10.1088/1755-1315/491/1/012048