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What is Enhanced Grey Wolf Optimizer for Feature Selection about?

This research proposes a modified grey wolf optimizer with multi-solution crossover integration (MGWO-MCI) for feature selection, addressing limitations of the original Grey Wolf Optimizer (GWO) such as premature convergence and local optima trapping. The MGWO-MCI algorithm enhances solution diversity by incorporating additional wolves and a crossover operation, demonstrating superior performance on various datasets, achieving an accuracy of 98.6% on the NSL-KDD dataset. The study validates the effectivenes

Author

Prosecution Department

Language

EN