2023 – Enhancing Dam Safety Through Machine Learning-Assisted Deformation Forecasting

Huon A. W. Wilson

This research paper discusses the implementation and evaluation of machine learning algorithms for predicting deformation in dams, with the aim to provide key insights for dam safety engineers in their operations and maintenance schedules. The study evaluated both predictive models for deformation movements and classification models for critical deformation events. The findings highlight the potential of machine learning in this domain, while also emphasizing the importance of data quality and model calibration. Recommendations for future work and improved model robustness are provided.

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