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Dynamic sensor nodes selection strategy refers to the optimization for achieving the tradeoff between energy consumption and effective coverage rate, enhancing energy efficiency, enlarging the effective coverage rate and prolonging the lifetime of wireless sensor networks (WSN). This paper proposes a dynamic sensor nodes selection strategy, so-called HN-GA, which uses the genetic algorithm (GA) to implement global searching and adopts the Hopfield network (HN) to reduce the search space of GA and ensure the validity of each chromosome. For evaluating the sensor nodes selection results, a combined metric based on several practically feasible measures of the energy consumption and effective coverage rate is introduced. The simulation results verify that the proposed HN-GA algorithm performs well in dynamic sensor nodes selection. With the help of HN-GA based dynamic sensor nodes selection, the lifetime and the effective coverage performance of WSN can be significantly improved. Compared to GA and HN, HN-GA has better performance in regional convergence and global searching, and it can achieve dynamic sensor nodes selection optimization efficiently, robustly and rapidly.