|From||Jose Ondina <email@example.com>|
|Date||Thu, 21 Feb 2019 09:44:23 +0000|
A 3D ocean modelling at small scales is necessary to get correct and timely information of the changes incurring to ocean environment in order to predict the large catastrophic disturbances and take preventive actions to protect the equipment and human life, in particular in the coastal zones of the ocean.
However, high-resolution numerical modelling using the current deterministic approach requires processing of huge amount of data in real-time and put significant stress on computational resources.
For example, the doubling of a 3D model resolution requires a 10-fold increase in computing resources.
Modern artificial intelligence (AI) methods are successfully used in medical research and engineering. The use of AI methods allows combining the benefits of the deterministic approach (solving the equations of motion) and the statistical approach based on the empirical relationship of the model inputs and outputs.
However, despite the great popularity of the AI methods in many fields, there are some obstacles to adapting this to oceanography in a simple or straightforward way.
The aims of this PhD are:
The feasibility of the project is supported by both human (expertise of the supervisory team) and computing (HPC cluster) resources.
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