Robotics & Machine Learning Daily News2024,Issue(Aug.26) :94-95.

Study Findings from Shahid Beheshti University Advance Knowledge in Machine Lear ning (Optimizing the geometry of hunchbacked block-type gravity quay walls using non-linear dynamic analyses and supervised machine learning technique)

Robotics & Machine Learning Daily News2024,Issue(Aug.26) :94-95.

Study Findings from Shahid Beheshti University Advance Knowledge in Machine Lear ning (Optimizing the geometry of hunchbacked block-type gravity quay walls using non-linear dynamic analyses and supervised machine learning technique)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – A new study on artificial intelligence is now available. According to news originating fromTehran, Iran, by NewsRx co rrespondents, research stated, “In the present study, the seismic behavior of hunchbacked block-type gravity quay walls rested on non-liquefiable dense seabed s oil layer is investigated,and the optimal geometries for these wall types are p roposed by performing non-linear time history dynamicanalyses using Lagrangian explicit finite difference method. For this purpose, first, a reference numerical model of the hunchbacked quay wall is developed, and its seismic response is v alidated against thewell-documented physical model tests.”

Key words

Shahid Beheshti University/Tehran/Iran/Asia/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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