A self-adaptive intelligent single-particle optimizer compression algorithm

作者：Zeng; Jie

来源：Neural Computing & Applications, 2014, 25(6): 1285-1292.

DOI：10.1007/s00521-014-1609-x

• Data compression
• Codebook design
• Particle swarm optimization
• Intelligent single-particle optimizer
• DNA

This paper presents a self-adaptive intelligent single-particle optimizer (AdpISPO) for DNA sequence data compression codebook design. Featured with the crucial self-adaptive optimization process, AdpISPO is capable of attaining better fitness value than most existing particle swarm optimization variants with no specific parameters required. A novel DNA sequence data compression algorithm, namely BioSqueezer, is proposed in this paper. Introducing all the unique data features in constructing the compression codebook, BioSqueezer compresses DNA sequences by replacing similar fragments with the index of its corresponding code vector. For attaining higher compression ratio, the AdpISPO is employed in BioSqueezer for the codebook design. Experimental results on benchmark DNA sequences demonstrate that BioSqueezer attains better performance than other state-of-the-art DNA compression algorithms.

• 出版日期2014-11
• 单位深圳大学