Value Creation in the Utility Sector Using Machine Learning

  • Hansen, Bolette Dybkjær (PI (principal investigator))
  • Moeslund, Thomas B. (PI (principal investigator))
  • Jensen, David Getreuer (PI (principal investigator))

Projektdetaljer

Beskrivelse

This project aims to identify and analyse the potential for value creation in the intersection between machine learning and the utility sector, with focus on the water supply sector. The specific areas targeted are: Sewers, drains, climate and streams, wastewater treatment plant, clean water, energy, and software and economy within the water sector.
Kort titelMachine Learning in The Water Sector
StatusAfsluttet
Effektiv start/slut dato01/01/2019 → 31/12/2021

Samarbejdspartnere

  • Envidan A/S (Projektpartner)

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  • 1 Konferenceartikel i proceeding

  • General Sewer Deterioration Model Using Random Forest

    Hansen, B. D., Jensen, D. G., Rasmussen, S. H., Tamouk, J., Uggerby, M. & Moeslund, T. B., 2019, IEEE Symposium on Computational Intelligence for Engineering Solutions (IEEE CIES). IEEE, 8 s.

    Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

    5 Citationer (Scopus)