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基于惯性权重调整的果蝇优化算法在WSN中的应用

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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.
The Application of Fruit Fly Optimization Algorithm Based on Inertia Weight Adjustment in WSN
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 im-proved fruit fly optimization algorithm not only improves the convergence speed and global search capability,but also significantly improves the coverage of WSN.

wireless sensor networkimproved fruit fly optimization algorithminertia weight cosine adaptive adjustment strate-gylearning factor adjustment strategycoverage

孙若鹏、权悦、刘帅帅、国海、余雪茜

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安徽科技学院机械工程学院,安徽蚌埠 233030

安徽科技学院电气与电子工程学院,安徽蚌埠 233030

无线传感器网络 改进果蝇优化算法 惯性权重余弦自适应调整策略 学习因子调整策略 覆盖率

安徽省高校自然科学研究重大项目安徽省大学生创新创业训练计划项目

2022AH040234202210879063

2024

荆楚理工学院学报
荆楚理工学院

荆楚理工学院学报

影响因子：0.168
ISSN：1008-4657
年,卷(期)：2024.39(4)