Artificial Intelligence to Enhance Mission Science Output for In-situ Observations: Dealing with the Sparse Data Challenge

12/26/2022
by   M. I. Sitnov, et al.
0

In the Earth's magnetosphere, there are fewer than a dozen dedicated probes beyond low-Earth orbit making in-situ observations at any given time. As a result, we poorly understand its global structure and evolution, the mechanisms of its main activity processes, magnetic storms, and substorms. New Artificial Intelligence (AI) methods, including machine learning, data mining, and data assimilation, as well as new AI-enabled missions will need to be developed to meet this Sparse Data challenge.

READ FULL TEXT

page 1

page 2

research
01/21/2022

AiTLAS: Artificial Intelligence Toolbox for Earth Observation

The AiTLAS toolbox (Artificial Intelligence Toolbox for Earth Observatio...
research
07/05/2019

AI-based evaluation of the SDGs: The case of crop detection with earth observation data

The framework of the seventeen sustainable development goals is a challe...
research
08/06/2023

AI-GOMS: Large AI-Driven Global Ocean Modeling System

Ocean modeling is a powerful tool for simulating the physical, chemical,...
research
01/26/2016

A Survey on Artificial Intelligence and Data Mining for MOOCs

Massive Open Online Courses (MOOCs) have gained tremendous popularity in...
research
10/03/2009

Pre-processing in AI based Prediction of QSARs

Machine learning, data mining and artificial intelligence (AI) based met...
research
06/27/2021

Low power in-situ AI Calibration of a 3 Axial Magnetic Sensor

Magnetic surveys are conventionally performed by scanning a domain with ...
research
12/22/2021

Beyond Low Earth Orbit: Biomonitoring, Artificial Intelligence, and Precision Space Health

Human space exploration beyond low Earth orbit will involve missions of ...

Please sign up or login with your details

Forgot password? Click here to reset