Cite this DOI

Longman Publishers (2020). Three Swarm Intelligence Algorithms for Wireless Sensor Network Applications: A review. *Journal of Science & Technology*, 80–86. https://doi.org/10.46243/jst.2020.v5.i6.pp80-86

@article{anon2020three,
  title     = {{Three Swarm Intelligence Algorithms for Wireless Sensor Network Applications: A review}},
  journal   = {Journal of Science \& Technology},
  year      = {2020},
  month     = {oct},
  number    = {Volume 5},
  pages     = {80--86},
  publisher = {Longman Publishers},
  issn      = {2456-5660},
  doi       = {10.46243/jst.2020.v5.i6.pp80-86},
  url       = {https://doi.org/10.46243/jst.2020.v5.i6.pp80-86},
  language  = {en},
  abstract  = {: Wireless Sensor Networks (WSNs) are increasingly realizing applications in IoT, smart grids, healthcare, security, swarm robotics, etc. Swarm Intelligence is used to optimize performance parameters associated with WSNs including localization, coverage, network lifetime, energy efficiency to name a few. The scope of this paper is restricted to a survey on Stochastic Diffusion Search, Genetic Algorithm and Particle Swarm Algorithm with respect to their organization and capacity to optimize these network parameters and their current as well as potential applications in WSNs.}
}

TY  - JOUR
TI  - Three Swarm Intelligence Algorithms for Wireless Sensor Network Applications: A review
JO  - Journal of Science & Technology
PY  - 2020
DA  - 2020/10/05/
IS  - Volume 5
SP  - 80
EP  - 86
PB  - Longman Publishers
SN  - 2456-5660
LA  - en
AB  - : Wireless Sensor Networks (WSNs) are increasingly realizing applications in IoT, smart grids, healthcare, security, swarm robotics, etc. Swarm Intelligence is used to optimize performance parameters associated with WSNs including localization, coverage, network lifetime, energy efficiency to name a few. The scope of this paper is restricted to a survey on Stochastic Diffusion Search, Genetic Algorithm and Particle Swarm Algorithm with respect to their organization and capacity to optimize these network parameters and their current as well as potential applications in WSNs.
DO  - 10.46243/jst.2020.v5.i6.pp80-86
UR  - https://doi.org/10.46243/jst.2020.v5.i6.pp80-86
ER  -

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    "URL": "https://doi.org/10.46243/jst.2020.v5.i6.pp80-86",
    "title": "Three Swarm Intelligence Algorithms for Wireless Sensor Network Applications: A review",
    "source": "Smart Scholars DOI Registry",
    "container-title": "Journal of Science & Technology",
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    "language": "en",
    "abstract": ": Wireless Sensor Networks (WSNs) are increasingly realizing applications in IoT, smart grids, healthcare, security, swarm robotics, etc. Swarm Intelligence is used to optimize performance parameters associated with WSNs including localization, coverage, network lifetime, energy efficiency to name a few. The scope of this paper is restricted to a survey on Stochastic Diffusion Search, Genetic Algorithm and Particle Swarm Algorithm with respect to their organization and capacity to optimize these network parameters and their current as well as potential applications in WSNs.",
    "ISSN": "2456-5660"
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From the record as registered (version 2) — the record and its history. Programs: https://registry.smartscholars.in/api.php?action=cite&doi=10.46243%2Fjst.2020.v5.i6.pp80-86 gives all four in one JSON answer.