An Efficient Autolanding Control Model Using Modified Black Widow Optimization Based Hybrid Deep Neural Network

Hybrid black widow optimization with iterated greedy algorithm for gene selection problems

“…It has been used in various applications and demonstrates its ability to deal with a variety of problems in various fields of engineering optimization, for example, document clustering, cloud computing optimization, and information retrieval. As well, it has the capability to deal with the challenges of real-world optimization, the ability to have a high degree of convergence, and the ability to offer a high-quality performance [ [65] , [66] , [67] , [68] , [69] , [70] , [71] , [72] ]. For that, BWO was applied for GS in two ways: it was employed in its original form, and it was hybridized with an iterated greedy (IG) algorithm, BWO-IG, to improve the BWO's local search capabilities.…”