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Models and Sensor Data

Can we reliably forecast and manage urban flooding with a machine learning model? That was a question that was raised at Deltares, a knowledge institute for water and the subsurface. Initial research was promising. As VORtech is building up its expertise in machine learning for physics-based modelling, we welcomed the opportunity to join Deltares and Delft University of Technology in further explorations.

Models and sensor data are an indispensible combination. Sensor data is needed to validate models and the models are often necessary to understand and extrapolate the data. VORtech has been working a two very exciting projects in the past few months in which sensor data and models are combined in an innovative application.

The Summer school "Data Assimilation and its Applications in Oceanography, Hydrology, Risk & Safety and Reservoir Engineering" in Sibiu, Romania.

On Thursday February 23, 2017, VORtech hosted our first Meetup on Data Science: "Data Science in Industry"

Groundwater flow models require proper setting of parameters. Obtaining optimal settings based on measurement by using the OpenDA data-assimilation tool.