Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Maurizio Righetti"'
Publikováno v:
Energies, Vol 14, Iss 17, p 5344 (2021)
Modelling heat load is a crucial challenge for the proper management of heat production and distribution. Several studies have tackled this issue at building and urban levels, however, the current scale of interest is shifting to the district level d
Externí odkaz:
https://doaj.org/article/0b85a5dc0d8c444a8937bfadb8b16bbc
Publikováno v:
Applied Sciences, Vol 11, Iss 9, p 4290 (2021)
The evolution of smart water grids leads to new Big Data challenges boosting the development and application of Machine Learning techniques to support efficient and sustainable drinking water management. These powerful techniques rely on hyperparamet
Externí odkaz:
https://doaj.org/article/107e32782dde478da69097a57ae14f37
Autor:
Andrea Menapace, Ariele Zanfei, Manuel Felicetti, Diego Avesani, Maurizio Righetti, Rudy Gargano
Publikováno v:
Applied Sciences, Vol 10, Iss 22, p 8219 (2020)
Developing data-driven models for bursts detection is currently a demanding challenge for efficient and sustainable management of water supply systems. The main limit in the progress of these models lies in the large amount of accurate data required.
Externí odkaz:
https://doaj.org/article/e925fb1b353f4050ba8701d4ae92923b
Publikováno v:
Applied Sciences, Vol 11, Iss 4290, p 4290 (2021)
Applied Sciences
Volume 11
Issue 9
Applied Sciences
Volume 11
Issue 9
The evolution of smart water grids leads to new Big Data challenges boosting the development and application of Machine Learning techniques to support efficient and sustainable drinking water management. These powerful techniques rely on hyperparamet