公开(公告)号：US20210248466A1

公开(公告)日：2021-08-12

申请号：US17169849

申请日：2021-02-08

Applicant: SUNTRACKER TECHNOLOGIES LTD.

Inventor： Ian Edward Ashdown ,  Oleksandr Ponomarov

IPC: G06N3/08 ,  G06N3/04

Abstract: A system and method for a neural network that is trained to recognize patterns in the exitance convergence behaviour of a radiosity equation being solved for a set of finite element environments, and subsequently employed to monitor and predict the exitance convergence behaviour of novel finite element environments. The neural network is trained with feature vectors representing partial snapshots of exitance vectors at various iterations in a radiosity calculation. The feature vectors are related to numbers of iterations that can be skipped by making approximate calculations instead of performing the iterations. In use, when a radiosity equation is being solved, the neural network identifies feature vectors generated during the calculations that signify that a certain number of iterations can be skipped by making an approximate calculation.

公开(公告)号：US11093831B1

公开(公告)日：2021-08-17

申请号：US17169849

申请日：2021-02-08

Applicant: SUNTRACKER TECHNOLOGIES LTD.

Inventor： Ian Edward Ashdown ,  Oleksandr Ponomarov

IPC: G06N3/08 ,  G06N3/04 ,  G06F30/13

Abstract: A system and method for a neural network that is trained to recognize patterns in the exitance convergence behaviour of a radiosity equation being solved for a set of finite element environments, and subsequently employed to monitor and predict the exitance convergence behaviour of novel finite element environments. The neural network is trained with feature vectors representing partial snapshots of exitance vectors at various iterations in a radiosity calculation. The feature vectors are related to numbers of iterations that can be skipped by making approximate calculations instead of performing the iterations. In use, when a radiosity equation is being solved, the neural network identifies feature vectors generated during the calculations that signify that a certain number of iterations can be skipped by making an approximate calculation.