Data-Based Models for the Prediction of Dam Behaviour: A Review and Some Methodological Considerations
By F. Salazar, R. Morán, M. Toledo, Eugenio Oñate. 2017
327 citations recorded by the source corpus.
AbstractPredictive models are an important element in dam safety analysis. They provide an estimate of the dam response faced with a given load combination, which can be compared with the actual measurements to draw conclusions about dam safety. In addition to numerical finite element models, statistical models based on monitoring data have been used for decades for this purpose. In particular, the hydrostatic-season-time method is fully implemented in engineering practice, although some limitations have been pointed out. In other fields of science, powerful tools such as neural networks and support vector machines have been developed, which make use of observed data for interpreting complex systems . This paper contains a review of statistical and machine-learning data-based predictive models, which have been applied to dam safety analysis . Some aspects to take into account when developing analysis of this kind, such as the selection of the input variables, its division into training and validation sets, and the error analysis, are discussed. Most of the papers reviewed deal with one specific output variable of a given dam typology and the majority also lack enough validation data. As a consequence, although results are promising, there is a need for further validation and assessment of generalisation capability. Future research should also focus on the development of criteria for data pre-processing and model application.
Subfields: Civil and Structural Engineering
View Paper: https://www.semanticscholar.org/paper/e7ffe465fadfb051dd3955167dbbed4386a797eb
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In Civil and Structural Engineering
Citations in the corpus
- An Empirical Comparison of Multiple Linear Regression and Artificial Neural Network for Concrete Dam Deformation Modelling (2019, background): “Introduction Deformation modelling is an important component of dam safety systems, both for the daily operation and for longterm behavior evaluation [1].”
- A Survey of Deep Learning and Its Applications: A New Paradigm to Machine Learning (2019, background): “Salazar et al. [52] presented a review on the statistical and machine learning based predictive models which are required for the dam safety analysis.”