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Description
  • Wireless sensor nodes with the capability to harvest energy from their environment are well suited for outdoor environmental monitoring applications. Due to their very nature, they can map spatial and temporal characteristics of the environment with high resolution. This, in turn, contributes to a better understanding of the processes and phenomena in the environment under surveillance. However, their energy-efficient operation is not a straightforward task. In this work, we use two bio-inspired optimization methods for a simulation-driven optimization of wireless sensor node parameters with respect to their performance at the intended deployment location.
  • Wireless sensor nodes with the capability to harvest energy from their environment are well suited for outdoor environmental monitoring applications. Due to their very nature, they can map spatial and temporal characteristics of the environment with high resolution. This, in turn, contributes to a better understanding of the processes and phenomena in the environment under surveillance. However, their energy-efficient operation is not a straightforward task. In this work, we use two bio-inspired optimization methods for a simulation-driven optimization of wireless sensor node parameters with respect to their performance at the intended deployment location. (en)
Title
  • Optimization of Wireless Sensor Node Parameters by Differential Evolution and Particle Swarm Optimization
  • Optimization of Wireless Sensor Node Parameters by Differential Evolution and Particle Swarm Optimization (en)
skos:prefLabel
  • Optimization of Wireless Sensor Node Parameters by Differential Evolution and Particle Swarm Optimization
  • Optimization of Wireless Sensor Node Parameters by Differential Evolution and Particle Swarm Optimization (en)
skos:notation
  • RIV/61989100:27740/14:86092374!RIV15-MSM-27740___
http://linked.open...avai/riv/aktivita
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  • P(ED1.1.00/02.0070), P(EE.2.3.20.0073), S
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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  • 34999
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  • RIV/61989100:27740/14:86092374
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  • particle swarm optimization; differential evolution; parameter optimization; wireless sensor networks (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [2D87631DC3B5]
http://linked.open...v/mistoKonaniAkce
  • Ostrava
http://linked.open...i/riv/mistoVydani
  • Berlin Heidelberg
http://linked.open...i/riv/nazevZdroje
  • Advances in Intelligent Systems and Computing. Volume 303
http://linked.open...in/vavai/riv/obor
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  • Krömer, Pavel
  • Musílek, Petr
  • Prauzek, Michal
  • Bartoň, Tomas
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http://linked.open.../riv/zahajeniAkce
issn
  • 2194-5357
number of pages
http://bibframe.org/vocab/doi
  • 10.1007/978-3-319-08156-4_2
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  • Springer-Verlag. (Berlin; Heidelberg)
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  • 978-3-319-08155-7
http://localhost/t...ganizacniJednotka
  • 27740
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