“Machine learning: an engineering perspective and some applications in combination with numerical modelling”

Machine Learning (ML) is an emerging technology with applications in multiple fields. The concepts and techniques developed in the community of computer science is now in use by an increasing set of disciplines. The common feature of all applications of ML is the need for data for model fitting. These data may come from sensors, but they can also be generated with numerical models.

The benefits of these tools attracted the attention of the numerical modelling community. As an example, 9 minisimposia were specifically focused on ML in the last 14th World Congress in Computational Mechanics. However, there is still a lack of communication between both disciplines: there is some confusion regarding the terms used, the possibilities of the technology and its true potential. A similar situation exists in practical civil engineering: the approach is becoming popular, but many practitioners are still reluctant to modify their traditional procedures.

In this seminar, some concepts related to machine learning will be discussed from a practical engineering viewpoint. In addition, examples of application in different settings will be presented, both alone and in combination with numerical models.

Read more on cimne.com/vnews/11316

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