A Neural Network for the Identification of Dangerous Planetesimals (Including scripts for data generation)

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Ada Coda
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A Neural Network for the Identification of Dangerous Planetesimals (Including scripts for data generation)

Post by Ada Coda » Tue Jan 30, 2018 2:07 pm

A Neural Network for the Identification of Dangerous Planetesimals (Including scripts for data generation)

Abstract: Two neural networks were designed to identify hazardous planetesimals that were trained on object trajectories calculated in a cloud computing environment. The first neural network was fully-connected and was trained on the orbital elements (OEs) of real/simulated planetesimals, while the second was a 1-dimensional convolutional neural network that was trained on the position Cartesian coordinates of real/simulated planetesimals. Ultimately, the network trained on OEs had a better performance by identifying one-third of known potentially hazardous objects including the 3 asteroids with the highest chance of impact with Earth (2009 FD, 1999 RQ36, 1950 DA) as established by NASA's Monte Carlo based Sentry system.

Credit: Hefele, John

Site: https://github.com/mrteetoe/HOI
Last edited by Ada Coda on Tue Apr 30, 2019 8:29 pm, edited 1 time in total.
Reason: Updated code entry.

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