Opinion-based Filtering through Trust. | eXiT Research Group - Universitat de Girona

Skip to content

Català
Español
English

Control Engineering and Intelligent Systems

Home
About us
- Team
- Recognition / Awards
Research
Technology transfer
Contact
Vacancies
Search

Search

Menu

Publications

Home » publication » Opinion-based Filtering through Trust.

Montaner, M.; Lopez, B.; de la Rosa, J. LL.
Lecture Notes in Computer Science 2446 (2002): 164-178.
Year: 2002

Contact Information

Universitat de Girona
Campus Montilivi
Escola Politècnica Superior (Edifici P4)
Carrer Universitat de Girona, 6
17003 – Girona (Spain)
exit@udg.edu

Certified by...

eXiT Research group - Control Engineering and Intelligent Systems (IIiA - UdG)

El projecte CLIMA té com a objectiu promoure el desenvolupament de comunitats energètiques com a actors rellevants en la cadena de valor energètica, amb un enfocament en la regió de Girona (Catalunya).

Visita la pàgina web 👉 https://clima.udg.edu/

The Energy Forecaster tool provides hourly forecasting of electrical/loads and Photovoltaic/wind generation. Two forecasting horizons are provided: intra-day and day-ahead. Forecasts are based on weather data, characteristics of generation assets, and contextual information. Occupancy also can be considered as an input for forecasting. The application is fully integrable in the Energy Management System.

More information: https://elandh2020.eu/ and https://exit.udg.edu/

This project has received funding from the European Union’s Horizon 2020 Research and Innovation programme under Grant Agreement No 824388

The Optimal Scheduler tool provides an hourly scheduling of storage (when
store or consume) and controllable assets (when switch on/off) in order to maximize the use of renewable energy resources. It is based on the forecast production/consumption in the Local Energy System (LES). The application is fully integrable in the Energy Management System. This tool is part of the E-LAND project.

More information: https://elandh2020.eu/ and https://exit.udg.edu/

This project has received funding from the European Union’s Horizon 2020 Research and Innovation programme under Grant Agreement No 824388

A brief introduction to fault detection, location, and diagnosis with Principal Component Analysis (PCA).

Laiz Souto

2026 by eXiT (UdG). All rights reserved. Legal information - Privacy policy - Cookie policy

Home
About us
- Team
- Recognition / Awards
Research
Technology transfer
Contact
Vacancies

We use cookies on our website to give you the most relevant experience by remembering your preferences and repeat visits. By clicking “Accept”, you consent to the use of ALL the cookies.

Cookie settings ACCEPT REJECT

Privacy & Cookies Policy

Privacy Overview

This website uses cookies to improve your experience while you navigate through the website. Out of these cookies, the cookies that are categorized as necessary are stored on your browser as they are essential for the working of basic functionalities of the website. We also use third-party cookies that help us analyze and understand how you use this website. These cookies will be stored in your browser only with your consent. You also have the option to opt-out of these cookies. But opting out of some of these cookies may have an effect on your browsing experience.

Necessary

Necessary

Always Enabled

Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.

Non-necessary

Non-necessary

Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.

SAVE & ACCEPT