DocumentCode
2307949
Title
Combining neural networks and ARIMA models for hourly temperature forecast
Author
Hippert, Henrique S. ; Pedreira, Carlos E. ; Souza, Reinaldo C.
Author_Institution
Dept. of Stat., Univ. Federal do Juiz de Fora, Brazil
Volume
4
fYear
2000
fDate
2000
Firstpage
414
Abstract
This paper proposes a hybrid forecasting system that combines linear models and multilayer neural networks to forecast hourly temperatures based on the past observed temperatures and the maximum and minimum forecast temperatures supplied by the weather service. First, a simple autoregressive model is built for the temperature series. Numerical results, using real data is reported
Keywords
autoregressive moving average processes; feedforward neural nets; time series; weather forecasting; ARIMA models; autoregressive model; hourly temperature forecast; learning; multilayer neural networks; time series; weather forecasting; Electricity supply industry; Interpolation; Load forecasting; Multi-layer neural network; Neural networks; Predictive models; Space cooling; Space heating; Temperature; Weather forecasting;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on
Conference_Location
Como
ISSN
1098-7576
Print_ISBN
0-7695-0619-4
Type
conf
DOI
10.1109/IJCNN.2000.860807
Filename
860807
Link To Document