Izvorni znanstveni članak
https://doi.org/10.2478/otmcj-2020-0009
Application of time series models for heating degree day forecasting
Merve Kuru
Gulben Calis
orcid.org/0000-0003-3056-4870
; Ege University, Department of Civil Engineering, Bornova, Izmir, 35040, Turkey.
Sažetak
This study aims at constructing short-term
forecast models by analyzing the patterns of the heating
degree day (HDD). In this context, two different time series
analyses, namely the decomposition and Box–Jenkins
methods, were conducted. The monthly HDD data in
France between 1974 and 2017 were used for analyses. The
multiplicative model and 79 SARIMA models were constructed by the decomposition and Box–Jenkins method,
respectively. The performance of the SARIMA models was
assessed by the adjusted R2
value, residual sum of squares,
the Akaike Information Criteria, the Schwarz Information
Criteria, and the analysis of the residuals. Moreover, the
mean absolute percentage error, mean absolute deviation, and mean squared deviation values were calculated
to evaluate the performance of both methods. The results
show that the decomposition method yields more acceptable forecasts than the Box–Jenkins method for supporting short-term forecasting of the HDD.
Ključne riječi
heating degree days; short-term forecasting; time series; Box–Jenkins method; SARIMA models
Hrčak ID:
243171
URI
Datum izdavanja:
1.2.2020.
Posjeta: 686 *