Abstract
Aiming at the uneven random coverage distribution of wireless sensor networks sensor nodes, the sparrow search algorithm (SSA) is used to optimize the node coverage of wireless sensor networks. To improve the global search capability of SSA, the algorithm is improved and applied to the wireless sensor networks of bridge monitoring. For enhancing the coverage of the wireless sensor networks, this article uses two improved methods. One is to use the good point set theory to make the initial population evenly distributed; another is to introduce a weight factor to speed up its convergence. The experiments have proved the reliability and rationality of the algorithm. The improved algorithm is superior to other meta-heuristic algorithms and provides a new idea for optimizing bridge monitoring wireless sensor networks coverage.
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