Stefano Frigiola
Robust Bootstrap and GARCH process application for heating demand in Germany.
Rel. Franco Pellerey, Abdelhak M. Zoubir. Politecnico di Torino, Corso di laurea magistrale in Communications And Computer Networks Engineering (Ingegneria Telematica E Delle Comunicazioni), 2022
|
Preview |
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (4MB) | Preview |
Abstract
Energy, in all its forms, is a physical quantity without which man could not carry out all his daily activities. However, nowadays, we hear more and more about problems due to lack or waste of energy due to the misuse by man and also due to an exaggerated consumption of it. Making energy forecasts is therefore something that would allow man to balance what is required and consumed by energy without encountering problems of overproduction and shortage. To do this, increasingly sophisticated algorithms are created to allow companies that supply energy to stipulate plans for forecasting consumption, demand, and production of energy itself, allowing them to better manage economic and environmental resources.
In the following, two main methods are reported: the classical residual bootstrap and the influence function bootstrap
Relatori
Anno Accademico
Tipo di pubblicazione
Numero di pagine
Corso di laurea
Classe di laurea
Ente in cotutela
Aziende collaboratrici
URI
![]() |
Modifica (riservato agli operatori) |
