.png){kind=icon}
返回
Elephant Herding Optimization for Energy-Based Localization
.png){kind=icon}
OA
AI
DOI：10.3390/s18092849.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This work addresses the energy-based source localization problem in wireless sensors networks. Instead of circumventing the maximum likelihood (ML) problem by applying convex relaxations and approximations, we approach it directly by the use of metaheuristics. To the best of our knowledge, this is the first time that metaheuristics are applied to this type of problem. More specifically, an elephant herding optimization (EHO) algorithm is applied. Through extensive simulations, the key parameters of the EHO algorithm are optimized such that they match the energy decay model between two sensor nodes. A detailed analysis of the computational complexity is presented, as well as a performance comparison between the proposed algorithm and existing non-metaheuristic ones. Simulation results show that the new approach significantly outperforms existing solutions in noisy environments, encouraging further improvement and testing of metaheuristic methods.
Keyword:
nature inspired algorithms
swarm optimization
elephant search algorithm
energy-based localization
acoustic positioning
wireless sensor networks
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.5
论文数:
7.2W
被引数:
20.9W
机构
引用论文
分享收藏分享收藏Cultures of Circulation and the Urban Imaginary: Miami as Example and Exemplar环流文化与城市想象：迈阿密作为实例与典范
PREAI
分享收藏URETEROCALYCOSTOMY IN THE MANAGEMENT OF RENAL AND URETERIC TRAUMA: REPORT OF A CASE输尿管肾盂吻合术在肾和输尿管创伤管理中的应用：病例报告
PREAI
分享收藏The Staphylococcus aureus CamS lipoprotein is a repressor of toxin production that shapes host-pathogen interaction.png)
PLOS Biology
OAAI
PLOS BiologyIF0
OAAI分享收藏
查看更多内容