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Buoyancy and Stability for Submerged and Floating Bodies01:11

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In fluid mechanics, buoyancy and stability are key concepts for understanding the behavior of submerged and floating bodies. When a stationary body is fully or partially submerged in a fluid, the fluid exerts a force on the body known as the buoyant force. This force acts vertically upward through a point called the center of buoyancy, which is the center of the displaced fluid volume. According to Archimedes' principle, the magnitude of the buoyant force is equal to the weight of the fluid...
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一个智能生物启发的自主监控系统,使用水下传感器网络.

Shadab Khan1, Yash Veer Singh2, Prasant Singh Yadav3

  • 1Department of Computer Science & Engineering, ABES Engineering College, Ghaziabad 201009, India.

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概括
此摘要是机器生成的。

这项研究提出了一个智能生物灵感系统用于水下传感器网络,以提高能源效率. 与现有方法相比,tunicate swarm算法增强了集群头的选择,延长了网络寿命.

关键词:
生物启发的算法是生物启发的算法.集群头是一个集群头.能源效率是指能效的能源效率.路由 路由 路由 路由 路由水下传感器网络是水下传感器网络.

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科学领域:

  • 水下传感器网络是水下传感器网络.
  • 生物启发的计算技术
  • 网络协议 网络协议

背景情况:

  • 在水下传感器网络 (USN) 中,能源效率至关重要.
  • 水下环境给网络寿命和数据通信带来了独特的挑战.
  • 由于信号传播速度缓慢,与地面网络不同,需要新的协议.

研究的目的:

  • 提出一个智能生物灵感自主监控系统,用于USN.
  • 提高能源效率并延长USN的网络寿命.
  • 引入一种高效的数据通信方法,使用一个用于集群头选举的化群群算法.

主要方法:

  • 运用了连衣群算法 (TSA) 进行智能集群头 (CH) 选举.
  • 考虑能量,距离和密度作为CH选择的关键参数.
  • 实现了一个基于层和集群内的传感器节点 (SN) 适应性值的旋转CH机制.

主要成果:

  • 与EE-LHCR,EE-DBR和DBR相比,拟议的协议证明了网络寿命的改善.
  • 基于TSA的CH选举有效地在SNs中实现了能源平衡.
  • 由于优化了能源分配,该系统实现了更长的网络寿命.

结论:

  • 拟议的智能生物启发系统显著提高了USN的能源效率.
  • 基于TSA的CH选择方法导致更平衡的能源分配和延长网络运行时间.
  • 这种方法为改善水下传感器网络的寿命和性能提供了有希望的解决方案.