Machine Learning-Based Seismic Damage Assessment of a Bridge Portfolio in Cohesive Soil

This study investigates the application of machine learning (ML) algorithms for seismic damage classification of bridges supported by helical pile foundations in cohesive soils. While ML techniques have shown strong potential in seismic risk modeling, most prior research has focused on regression ta...

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Bibliographic Details
Main Authors: Burak Ozturk, Ahmed Fouad Hussein, Mohamed Hesham El Naggar
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Buildings
Subjects:
Online Access:https://www.mdpi.com/2075-5309/15/10/1682
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