A new quantum chaotic cuckoo search algorithm for data clustering
作者：
Highlights：
• Quantum chaotic cuckoo search algorithm is proposed for the data clustering problem.
• The performance of the proposed approach was assessed on six well known datasets.
• The Chaos maps and Boundary handling strategy enhance the cuckoo search algorithm.
• The nonhomogeneous quantum update improves the global search ability.
• The significant superiority of the proposed algorithm over eight recent algorithms.
摘要
•Quantum chaotic cuckoo search algorithm is proposed for the data clustering problem.•The performance of the proposed approach was assessed on six well known datasets.•The Chaos maps and Boundary handling strategy enhance the cuckoo search algorithm.•The nonhomogeneous quantum update improves the global search ability.•The significant superiority of the proposed algorithm over eight recent algorithms.
论文关键词：Meta-heuristic,Optimization,Data clustering,Quantum cuckoo search,Chaotic map
论文评审过程：Received 2 August 2017, Revised 14 November 2017, Accepted 4 December 2017, Available online 5 December 2017, Version of Record 22 December 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.12.001
