PERFORMING SIMULATIONS USING MACHINE LEARNING

    公开(公告)号:US20230153604A1

    公开(公告)日:2023-05-18

    申请号:US17874050

    申请日:2022-07-26

    CPC classification number: G06N3/08 G06F30/27

    Abstract: To assist a machine learning environment in modelling a complex physical simulation (such as a numerical simulation or physics simulation), a correlation between input coordinates is determined. For example, a discrete solution (e.g., the correlation between the plurality of input coordinates) may be obtained from a non-discrete (e.g., continuous) physics space by performing a conversion from the physics space to a grid space. This correlation is input along with the coordinates into a machine learning environment to obtain results from the simulation. As a result, instead of implementing resource and power-intensive simulations to solve these computation problems, a machine learning environment implemented using less power and computing resources may solve these computation problems in a faster and more efficient manner.

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