Adaptive density peaking clustering algorithm combined with sparrow search algorithm

Chenwen Wu; Hengtong Li; Dandan Lei

doi:10.1117/12.3006156

10 October 2023 Adaptive density peaking clustering algorithm combined with sparrow search algorithm

Chenwen Wu, Hengtong Li, Dandan Lei

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127990T (2023) https://doi.org/10.1117/12.3006156
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Aiming at the problem that the density peak clustering algorithm (DPC) can not adaptively adjust the cutoff distance and the clustering center needs to be specified manually, an adaptive density peak clustering algorithm combined with sparrow search algorithm (ISSA-ADPC) is proposed. Firstly, the parameter of local density and relative distance is considered comprehensively, and the adaptive selection of cluster centers is realized according to the arrangement order and downward trend of parameter; Secondly, the homogenized distribution Chebyshev chaotic map is used to initialize the sparrow population, and then the adaptive t distribution strategy is introduced to improve the sparrow search algorithm, which avoids the algorithm falling into local optimization. At the same time, the improved sparrow search algorithm is used to realize the adaptive adjustment of cutoff distance; Finally, Compared with the experimental results of K-means, DBSCAN, DPC algorithm on the artificial and UCI datasets, the proposed algorithm has higher accuracy, adjusted rand index and adjusted mutual information values, and has better clustering performance.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Chenwen Wu, Hengtong Li, and Dandan Lei "Adaptive density peaking clustering algorithm combined with sparrow search algorithm", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127990T (10 October 2023); https://doi.org/10.1117/12.3006156

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KEYWORDS

Mathematical optimization

Flame

Algorithm development

Chaos

Iris

Iris recognition

Matrices

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