diplomsko delo
Denis Kotnik (Avtor), Matjaž Kukar (Mentor)

Povzetek

Prilagodljivo kratkoročno napovedovanje lokalnih vremenskih parametrov

Ključne besede

nevronska mreža;napaka;podatki;vremenski parameter;napoved;hitrost vetra;vrednost;cestnovremenska postaja;meteorologija;računalništvo;visokošolski strokovni študij;računalništvo in informatika;diplomske naloge;

Podatki

Jezik: Slovenski jezik
Leto izida:
Tipologija: 2.11 - Diplomsko delo
Organizacija: UL FRI - Fakulteta za računalništvo in informatiko
Založnik: [D. Kotnik]
UDK: 004.85(043.2)
COBISS: 1536010691 Povezava se bo odprla v novem oknu
Št. ogledov: 89
Št. prenosov: 22
Ocena: 0 (0 glasov)
Metapodatki: JSON JSON-RDF JSON-LD TURTLE N-TRIPLES XML RDFA MICRODATA DC-XML DC-RDF RDF

Ostali podatki

Sekundarni jezik: Angleški jezik
Sekundarni naslov: Adaptable short-term forecasting of local-weather parameters
Sekundarni povzetek: The goal of this research is to explore if we could improve the wind speed forecasts, with the regression methods and artificial neural networks. We utilized measurements data, which we obtained from road-weather stations of Direkcija Republike Slovenije za avtoceste and forecast data of INCA-CE system of Agencija Republike Slovenije za okolje. We used the Python programming language for the purpose of data preparation process. In the R programming environment we created the parameter error, which we defined as the difference between the predicted value for time t + ∆t and the measured value in time t+∆t. We predicted the error for subsequent 11 hours with the usage of regression methods and artificial neural networks, then we subtracted it from the INCA-CE predictions and visualised the results. We came to the conclusion that wind speed forecasts for 2014 could be corrected by up to 1 m/s in the early predicted hours with the usage of simple regression methods or neural networks.
Sekundarne ključne besede: neural network;error;data;weather parameter;forecast;wind speed;value;road weather station;meteorology;computer science;computer and information science;diploma;
Vrsta datoteke: application/pdf
Vrsta dela (COBISS): Diplomsko delo/naloga
Študijski program: 1000470
Komentar na gradivo: Univ. v Ljubljani, Fak. za računalništvo in informatiko
Strani: 87 str.
ID: 8739442