Modelling of FPGA-Particle Swarm Optimized GNSS Receiver for Satellite Applications

An efficient chaotic salp swarm optimization approach based on ensemble algorithm for class imbalance problems

“…By applying agents to reach an optimal solution, these algorithms adaptively check the feature space. The bio-inspired optimization algorithms have been widely used in feature selection such as Ant Colony Optimization (ACO) (Al-Ani 2005), Particle Swarm Optimization (PSO) (Xue et al 2012;Bewoor et al 2017;Amarendra and Reddy 2019;Namassivaya et al 2019) Artificial Bee Colony (ABC) (Schiezaro and Pedrini 2013;Sultanpure and Reddy 2018), Ant Lion Optimizier (ALO) (Emary et al 2016), cuckoo search algorithm (Thirugnanasambandam et al 2019), Salp Swarm Algorithm (SSA) (Ahmed et al 2018). The above algorithms have been widely used for feature selection but our study focus more on feature selection in imbalanced dataset.…”