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Intelligence Visualization for Wave Energy Power Generation
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2022 (English)In: 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW), IEEE, 2022, p. 986-987Conference paper, Published paper (Refereed)
Abstract [en]

Ocean waves provide a large amount of renewable energy, and Wave energy converter (WEC) can convert wave energy into electric en-ergy. This paper proposes a visualization platform for wave power generation. The platform can monitor various indicators of wave power generation in real time, combined with Long Short-Term Memory (LSTM) neural network to predict wave power and electric-ity consumption in real time and visualize monitoring data. The plat-form can intelligently allocate power generation equipment based on the power generation forecast data to achieve precise matching of power generation and power consumption, thereby improving overall power generation efficiency.

Place, publisher, year, edition, pages
IEEE, 2022. p. 986-987
Keywords [en]
Artificial intelligence, Human-centered computing-Visualization-Visualization design and evaluation methods, Human-centered computing-Visualization-Visualization techniques-Treemaps, Visualization, Wave power generation, Energy efficiency, Long short-term memory, Water waves, Wave energy conversion, Wave power, Design and evaluation methods, Human-centered computing, Human-centered computing-visualization-visualization design and evaluation method, Human-centered computing-visualization-visualization technique-treemap, Treemap, Visualization designs, Visualization technique, Wave energy
National Category
Other Engineering and Technologies Computer Systems Computer Engineering
Identifiers
URN: urn:nbn:se:uu:diva-474577DOI: 10.1109/VRW55335.2022.00344ISI: 000808111800337Scopus ID: 2-s2.0-85129615507ISBN: 9781665484022 (electronic)OAI: oai:DiVA.org:uu-474577DiVA, id: diva2:1658798
Conference
2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022, 12 March - 16 March 2022
Available from: 2022-05-17 Created: 2022-05-17 Last updated: 2022-09-05Bibliographically approved

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Lv, Zhihan

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CiteExportLink to record
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Citation style
  • apa
  • ieee
  • modern-language-association
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
  • text
  • asciidoc
  • rtf