Mining operational data for anomaly detection in buildings

Daniele Mauro Mazzarelli

Mining operational data for anomaly detection in buildings.

Rel. Alfonso Capozzoli, Marco Savino Piscitelli, Silvio Brandi. Politecnico di Torino, Master of science program in Energy And Nuclear Engineering, 2018

Preview

PDF (Tesi_di_laurea) - Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives.
Download (13MB) | Preview

Abstract:	Mining operational data for anomaly detection in buildings
Relators:	Alfonso Capozzoli, Marco Savino Piscitelli, Silvio Brandi
Academic year:	2017/18
Publication type:	Electronic
Number of Pages:	161
Subjects:
Corso di laurea:	Master of science program in Energy And Nuclear Engineering
Classe di laurea:	New organization > Master science > LM-30 - ENERGY AND NUCLEAR ENGINEERING
Aziende collaboratrici:	UNSPECIFIED
URI:	http://webthesis.biblio.polito.it/id/eprint/7355

Modify record (reserved for operators)