Prediction of soft proton intensities in the near-Earth space using machine learning.
Elena A. KronbergTanveer HannanJens HuthmacherMarcus MünzerFlorian PesteZiyang ZhouMax BerrendorfEvgeniy FaermanFabio GastaldelloSimona GhizzardiPhilippe EscoubetStein HaalandArtem SmirnovNithin SivadasRobert C. AllenAndrea TiengoRaluca IliePublished in: CoRR (2021)
Keyphrases
- machine learning
- prediction accuracy
- artificial intelligence
- machine learning methods
- pattern recognition
- low dimensional
- prediction model
- feature selection
- space time
- decision trees
- information extraction
- natural language processing
- data mining
- prediction algorithm
- machine learning algorithms
- text classification
- search space
- computer vision
- learning algorithm
- knowledge acquisition
- model selection
- data analysis
- knowledge base
- learning problems
- prediction error
- monte carlo simulation
- higher dimensional
- neural network
- predictive modeling