Coverage hole detection method of wireless sensor network based on clustering algorithm-Reference-Cited by-同舟云学术

Coverage hole detection method of wireless sensor network based on clustering algorithm

Published:2021-07 Issue: Volume:179 Page:109449
ISSN:0263-2241
Container-title:Measurement
language:en
Short-container-title:Measurement

Author:

Wang Feifei,Hu Haifeng

Funder

Henan Provincial Science and Technology Research Project

Publisher

Elsevier BV

Subject

Applied Mathematics,Electrical and Electronic Engineering,Condensed Matter Physics,Instrumentation

Reference27 articles.

1. Adhesion force sensing and activation of a membrane-bound sensor to activate nisin efflux pumps in Staphylococcus aureus under mechanical and chemical stresses;Carniello;J. Colloid Interface Sci.,2017

2. Measurement duration and frequency impact objective light exposure measures;Ulaganathan;Optom. Vis. Sci.,2017

3. Translating molecular detections into a simple temperature test using a target-responsive smart thermometer;Zhang;Chem. Sci.,2018

4. Report: NIA workshop on measures of physiologic resiliencies in human aging;Hadley;J. Gerontol. A Biol. Sci. Med. Sci.,2018

5. Models to improve the non-destructive analysis of persimmon fruit properties by VIS/NIR spectrometry;Altieri;J. Sci. Food Agric.,2017

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Optimally sensors nodes selection for adaptive heterogeneous precision agriculture using wireless sensor networks based on genetic algorithm and extended kalman filter;Physical Communication;2024-04

2. A Two-Layer Control Framework for Persistent Monitoring of a Large Area With a Robotic Sensor Network;IEEE Access;2024

3. On the interest of artificial intelligence approaches in solving the IoT coverage problem;Ad Hoc Networks;2024-01

4. A Comparative Study of Coverage Hole Detection Techniques in Wireless Sensor Networks;RAiSE-2023;2023-12-10

5. Node position estimation based on optimal clustering and detection of coverage hole in wireless sensor networks using hybrid deep reinforcement learning;The Journal of Supercomputing;2023-06-17