Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (14): 57-61.DOI: 10.3778/j.issn.1002-8331.1906-0272

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Improved Quantum Search Algorithm and Its Application on Computation of Core

XIE Xuming, DUAN Longzhen, QIU Taorong, YANG Youfeng   

  1. College of Information Technology, Nanchang University, Nanchang 330031, China
  • Online:2020-07-15 Published:2020-07-14



  1. 南昌大学 信息工程学院,南昌 330031


The ratio of targets is significant, basically for most of quantum search algorithms, and these algorithms cannot be successfully implemented without knowing the ratio of targets beforehand. While, Grover auto-control searching algorithm avoids this problem effectively, but the drawback of this algorithm is that it has no improvement over the Grover quantum search on behalf of final success probability. Dedicated to solve the aforesaid problem, an improved algorithm is proposed, and also applied in the computation of core of rough sets, in this study. Based on simulative experiment, not only does the proposed algorithm iterate self-adaptively, but it also has an overall improvement on the success probability, which is constantly over 85%.

Key words: quantum search, self-adaptive, rough set, core, algorithm design



关键词: 量子搜索, 自适应, 粗糙集, 核属性, 算法设计