Hi Everyone,
I have a data set from NASA Jet Propulsion Laboratory for the "Diameters of the asteroids" that has fallen till now and from that I am trying to forecast future asteroids diameter through ML algorithms.
For this research I am not able to find many published papers. Can anyone guide me with this?
Thanks
Given that the shapes and sizes of asteroids that have been visited or imaged via radar are so varied, it is not clear that what you are trying to do is possible. Can you say more about what the inputs to your model would be and what you have found in the literature so far?
I am not quite sure, what the point of this activity is? The reason why diameters are falling, is likely attributed to the fact that instruments become better in detecting them. Thus, even smaller bodies can be detected. Meaning there has been an observational bias, which is corrected more and more. There are estimates about asteroid population sizes, but nothing certain.
Input into your model should be possibly those estimates (or their bases), rate of improved detection (e.g. mirror size of telescopes) and the relation of detected diameters in the past and how this improved. However, I am not sure if this is a task for machine learning. This could be another basis for an estimate, but since the exact distribution of sizes is unclear, it cannot be a definite prediction of sizes. I think it would be easier to analse known distributions and check for a pattern (e.g. Gauss).
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