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A self-adjusting representation-based multitask PSO for high-dimensional feature selection
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DOI：10.1016/j.swevo.2025.102084.png)
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Abstract
En 中文
• A self-adjusting representation-based multitask generation method is proposed. • A new knowledge transfer strategy is designed to promote the information exchange. • An adaptive re-initialization strategy is proposed to enhance the search abilities. • An elite feature-preserving strategy is designed to preserve key features.
Keywords:
multitask generation
knowledge transfer
adaptive re-initialization
feature preservation
self-adjusting representation
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