【摘要】 目的：针对无线传感器网络随机部署节点的区域覆盖和传感器节点能量消耗问题，提出一种基于惯性权重余弦自适应调整策略的改进果蝇优化算法。方法：该算法在果蝇优化算法基础上，通过引入惯性权重的学习因子调整策略，在线调整算法的搜索步长。结果：增强了果蝇个体的自适应性及全局搜索能力，从而实现全局最优。结论：仿真实验表明，提出的改进果蝇优化算法不仅提高了收敛速度和全局搜索能力，还显著提升了WSN的覆盖率。更多还原

【Abstract】 Objective:An improved fruit fly optimization algorithm based on an inertia weight cosine adaptive adjustment strategy is proposed for the area coverage and sensor node energy consumption problems of randomly deployed nodes in wireless sensor networks. Methods:The algorithm adjusts the search step of the algorithm online based on the fruit fly optimization algorithm by introducing a learning factor adjustment strategy for inertia weights. Results:The adaptivity of individual fruit fly and the global search ability are enhanced so as to achieve global optimality. Conclusions:Simulation experiments show that the proposed improved fruit fly optimization algorithm not only improves the convergence speed and global search capability, but also significantly improves the coverage of WSN.更多还原