Publications by authors named "Yinghang Xu"
The Whale Optimization Algorithm (WOA) is regarded as a classic metaheuristic algorithm, yet it suffers from limited population diversity, imbalance between exploitation and exploration, and low solution accuracy. In this paper, we propose the Spiral-Enhanced Whale Optimization Algorithm (SEWOA), which incorporates a nonlinear time-varying self-adaptive perturbation strategy and an Archimedean spiral structure into the original WOA. The Archimedean spiral structure enhances the diversity of the solution space, aiding the algorithm in escaping local optima.
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- * A new multi-view multi-label fast network is proposed, which uses two different views and incorporates advanced techniques for rapid and precise identification of six distinct phenotypic features.
- * The network achieved a high classification accuracy of 94.66% and an inference speed of 11.9 ms, demonstrating its effectiveness in accurately classifying Auricularia cornea fruiting bodies.