Jezik: | Slovenski jezik |
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Leto izida: | 2022 |
Tipologija: | 2.09 - Magistrsko delo |
Organizacija: | UM FERI - Fakulteta za elektrotehniko, računalništvo in informatiko |
Založnik: | [N. Uremović] |
UDK: | 519.2:004.8(043.2) |
COBISS: | 132919555 |
Št. ogledov: | 47 |
Št. prenosov: | 12 |
Ocena: | 0 (0 glasov) |
Metapodatki: |
Sekundarni jezik: | Angleški jezik |
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Sekundarni naslov: | Geospatial multivariate time series forecasting using convolutional reccurrent neural networks |
Sekundarni povzetek: | In this thesis we present a method for multivariate time series forecasting for geospatial data. We prepare an overview of existing methods for multivariate spatial time series forecasting. We present the theorethical background of the ConvLSTM neural network architecture and the concepts it is based on. By using ConvLSTM for geospatial time series forecasting, we account for both spatial and temporal dependencies in our data. We test the proposed method on the case of forecasting multiple variables of air pollution for multiple measurement stations and compare our results to related work. |
Sekundarne ključne besede: | Multivariate time series;geospatial data;time series forecasting;convolutional recurrent neural networks; |
Vrsta dela (COBISS): | Magistrsko delo/naloga |
Komentar na gradivo: | Univ. v Mariboru, Fak. za elektrotehniko, računalništvo in informatiko, Računalništvo in informacijske tehnologije |
Strani: | 1 spletni vir (1 datoteka PDF (VII, 36 f.)) |
ID: | 16309900 |