应用模糊逻辑构建自组织水下通信网络

Chandra Kant Gautam, Amit Kumar, Bhuvana J
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引用次数: 0

摘要

本文探讨了如何利用模糊逻辑构建自组织水下通信网络。模糊常识是一种计算逻辑,其中应用了近似值来代替特定值。由于模糊常识可以根据不一致、近似和没有明确参数的记录做出选择,因此在一些水下通信网络设计中得到了应用。本文的重点是层次模糊逻辑(HFL)及其在水下通信网络生产中的应用。HFL 通过使用基于模糊规则的结构,利用模糊常识在每一步做出选择,从而实现自我代理。通过 HFL,一个设备可以完全根据其周围环境和可用统计数据创建一个有准备的、可靠的对话网络。利用包括噪声级、移动目标的速度/距离和语言交换种类在内的统计数据,HFL 允许水下通信网络创建动态集群,以适应周围环境,并小心地将机器内的所有节点超链接起来。此外,HFL 还能检测因节点离开网络而导致的性能下降,以及克服这些变化的恢复技术。最后,研究对象讨论了 HFL 如何降低机器的复杂性,并概述了其应用方面的未来研究可能性。
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Applying Fuzzy Logic for Constructing Self-Organized Underwater Communication Networks
this text surveys the usage of fuzzy logic for constructing self-organized underwater communication networks. Fuzzy common sense is a type of computing logic where approximate in place of particular values are applied. Fuzzy common sense is utilized in several underwater communique network designs due to its potential of making choices primarily based on records that is inconsistent, approximate, and with out clear parameters. The emphasis of this text is on Hierarchical Fuzzy logic (HFL) and its use inside the production of underwater communique networks. HFL allows self-agency thru the use of fuzzy rulebased structures that make use of fuzzy common sense to make choices at each step. thru HFL, a gadget can create an prepared, dependable conversation network based totally on its surroundings and the statistics available. using statistics which includes noise stages, speed/distance of moving objectives, and verbal exchange variety, HFL permits underwater communique networks to create dynamic clusters that could adapt to the surroundings and carefully hyperlink all nodes inside the machine. in addition, HFL provides the ability to detect performance degradation resulting from nodes departing from the network, and restoration techniques to conquer those changes. eventually, the object discusses how HFL can reduce the complexity of the machine, and outlines future research possibilities in its application.
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