Project description
Neural networks aid plate tectonics modelling
The constraints of the Earth’s lithosphere net rotation with respect to the underlying mantle cannot be determined from oceanic crust, as it is destroyed by plate tectonics. On the other hand, plate tectonics have a self-organising and statistically predictable nature that can be taught to neural networks. The TEMPO project will produce estimates for net rotation by training networks to use current data on the Earth, synthetic data, and the rules of physics. They will thus generate proposals of tectonic motion and mantle convection that will be tested against geological data, contributing to further research and the modelling of plate tectonics.
Fields of science
- natural sciencescomputer and information sciencesdatabases
- natural sciencesearth and related environmental sciencesgeologyseismologyplate tectonics
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
Programme(s)
Funding Scheme
MSCA-IF-EF-ST - Standard EF
Coordinator
75230 Paris Cedex 05
France
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