Pregled bibliografske jedinice broj: 999868
Building Soft Sensors using Artificial Intelligence: Use Case on Daily Solar Radiation
Building Soft Sensors using Artificial Intelligence: Use Case on Daily Solar Radiation // IEEE SpliTech 2019 : 4th International Conference on Smart and Sustainable Technologies
Split: Fakultet elektrotehnike, strojarstva i brodogradnje Sveučilišta u Splitu, 2019. str. 1-6 doi:10.23919/SpliTech.2019.8783137 (predavanje, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 999868 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Building Soft Sensors using Artificial Intelligence:
Use Case on Daily Solar Radiation
Autori
Nižetić Kosović, Ivana ; Božić, Ana ; Mastelić, Toni ; Ivanković, Damir
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
IEEE SpliTech 2019 : 4th International Conference on Smart and Sustainable Technologies
/ - Split : Fakultet elektrotehnike, strojarstva i brodogradnje Sveučilišta u Splitu, 2019, 1-6
ISBN
978-953-290-091-0
Skup
4th International Conference on Smart and Sustainable Technologies (SpliTech)
Mjesto i datum
Bol, Hrvatska; Split, Hrvatska, 18.06.2019. - 21.06.2019
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
Soft sensors, artificial intelligence, artificial neural networks, solar radiation, hybrid model
Sažetak
The concept of a soft sensor, a software replacement for unavailable, delayed or simply an expensive physical sensor, has received a lot of attention in the last decade. Its ability to estimate values of an observed phenomenon based on the expert knowledge defined in a form of theoretical or empirical models gives it a wide application and considerably lower costs. Furthermore, with the advent of artificial intelligence and data mining, soft sensors can be built purely by extracting correlations between different sensor data. However, both approaches can lead to either overfitting or overgeneralization. In this paper, both approaches are compared and combined in order to utilize the best of both worlds. Procedure for building soft sensors is defined and evaluated on a real-world use case for estimating daily solar radiation. The results show the best performance on the artificial neural network with RMSE of 1.454 and RRMSE of 3.42%.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Ustanove:
Institut za oceanografiju i ribarstvo, Split,
Ericsson Nikola Tesla d.d.