Early detection of internal erosion in earth dams: combining seismic monitoring and convolutional AutoEncoders

Author:

Yousefpour Negin1ORCID,Fazel Mojtahedi Farid1

Affiliation:

1. University of Melbourne, Department of Infrastructure Engineering, Parkville, Australia

Funder

University of Melbourne’s Faculty of Engineering and IT

Publisher

Informa UK Limited

Subject

Geology,Geotechnical Engineering and Engineering Geology,Safety, Risk, Reliability and Quality,Building and Construction,Civil and Structural Engineering

Reference98 articles.

1. DEM modelling to assess internal stability of gap-graded assemblies of spherical particles under various relative densities, fine contents and gap ratios

2. A Review of Machine Learning and Deep Learning Techniques for Anomaly Detection in IoT Data

3. Earthen Embankment Breaching

4. Baldi, P. 2012. Autoencoders, Unsupervised Learning, and Deep Architectures.

5. Bank, D., N. Koenigstein, and R. Giryes. 2020. Autoencoders. arXiv preprint arXiv:2003.05991.

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1. Internal erosion process and its influence factors in widely graded loose soils due to rainfall infiltration;Frontiers in Earth Science;2024-08-16

2. Machine Learning Methods for Geotechnical Site Characterization and Scour Assessment;Transportation Research Record: Journal of the Transportation Research Board;2024-07-25

3. Bio-inspired Predictive Models Development for Strength Characterization of Cement Deep-Mixed Plastic Soils;International Journal of Geosynthetics and Ground Engineering;2024-01-18

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