[1]JIA Xuan,ZHOU Zhiping.A novel PSO-GGA for clustering based on pattern reduction[J].CAAI Transactions on Intelligent Systems,2016,11(4):561-566.[doi:10.11992/tis.201507026]
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A novel PSO-GGA for clustering based on pattern reduction
CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume:
11
Number of periods:
2016 4
Page number:
561-566
Column:
学术论文—机器学习
Public date:
2016-07-25
- Title:
- A novel PSO-GGA for clustering based on pattern reduction
- Keywords:
- pattern reduction; PSO; generalized genetic algorithm; clustering
- CLC:
- TP18
- DOI:
- 10.11992/tis.201507026
- Abstract:
- To address the flaws in clustering speed, this paper proposes a novel PSO-GGA clustering algorithm based on pattern reduction. To fully combine the pattern reduction method, the algorithm uses a generalized genetic algorithm in serial to improve the particle swarm optimization algorithm. This can increase the diversity of samples and protect patterns that need to be saved for compression. At the same time, to determine the number of particles needed to replace the poor particles an incremental strategy is employed. This fully embodies the PSO’s ability for rapid search optimization and the genetic algorithm’s advantage of a large search space. The experimental results show that the clustering time only required 20 percent compared to the original algorithm without showing any obvious decline in accuracy.
- References:
-
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1900-01-01