Zhangcan Huang

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This paper proposes a new multi-objective evolutionary algorithm, called neighborhood exploring evolution strategy (NEES). This approach incorporates the idea of neighborhood exploration together with other techniques commonly used in the multi-objective evolutionary optimization literature (namely, non-dominated sorting and diversity preservation(More)
It is known from single-objective optimization that hybrid variants of local search algorithms and evolutionary algorithms can outperform their pure counterparts. This holds, in particular, in continuous search spaces and for differentiable fitness functions. The same should be true in multi-objective optimization. This approach is started in this paper. An(More)
In this study, we propose a new tracking method that uses Three Temporal Difference (TTD) and the Mean Algorithm (MA) to approach the tracking of an object. TTD method is used for continuous image subtraction while the MA method is used for the extraction of Background image. The proposed method was compared with different methods used in the field; the(More)
In this paper, we analyze an immunization strategy in SEIQ (susceptible, eclipse, infected, quarantine) model in small-world networks by associating the immunization probability with the infection probability. First, based on the mean-field theory, we establish the transmission dynamics equation for SEIQ model and find the relevant critical threshold of(More)