The author introduces FSDR, a deep learning-based feature selection algorithm tailored for Pseudo Time-Series (PTS) data. FSDR utilizes discrete relaxation to learn important features as model parameters efficiently.
Efficiently selecting informative features enhances multi-agent localization accuracy.
The proposed Frog-Snake Prey-Predation Relationship Optimization (FSRO) algorithm models the prey-predation relationship between frogs and snakes to solve discrete optimization problems, particularly feature selection in machine learning.