Binary Optimization Using Hybrid Grey Wolf Optimization for Feature Selection

A binary version of the hybrid grey wolf optimization (GWO) and particle swarm optimization (PSO) is proposed to solve feature selection problems in this paper. The original PSOGWO is a new hybrid optimization algorithm that benefits from the strengths of both GWO and PSO. Despite the superior perfo...

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Veröffentlicht in:	IEEE access 2019, Vol.7, p.39496-39508
Hauptverfasser:	Al-Tashi, Qasem, Abdul Kadir, Said Jadid, Rais, Helmi Md, Mirjalili, Seyedali, Alhussian, Hitham
Format:	Artikel
Sprache:	eng
Schlagworte:	classification Classification algorithms Computing time Data mining Feature extraction Feature selection Genetic algorithms grey wolf optimization hybrid binary optimization Optimization Optimization algorithms Particle swarm optimization Performance evaluation Search problems Simulated annealing
Online-Zugang:	Volltext
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