What is it about?
This research proposes the golden annealing crossover-mutation mayfly algorithm (GSASMA) , it has better search ability and stability. The global and local search are balanced. The GSASMA-SVM classifier achieves better accuracy in single channel recognition of P300 signals.
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Why is it important?
The GSASMA algorithm is faster convergence than existing MA algorithm. The GSASMA uses better positions for the mayflies, and has improved crossover and mutation operators. Based on a new feature extraction method, multi-time–frequency domain fusion, the GSASMA-SVM learner proposed in this paper offers new solutions and ideas for EEG signal recognition using an MA.
Perspectives
This work not only provides an idea for intelligent algorithm, but also has practical application significance in signal recognition.
Mengling Zhao
Xi'an University of Science and Technology
Read the Original
This page is a summary of: An improved mayfly algorithm and its application, AIP Advances, October 2022, American Institute of Physics,
DOI: 10.1063/5.0108278.
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