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%.

%U http://cea.ceaj.org/EN/10.3778/j.issn.1002-8331.1906-0272