Short Time Series Forecasting: Recommended Methods and Techniques

AudienciaPúblico en generales_ES
CoberturaMéxicoes_ES
Fecha de ingreso2026-09-15T00:30:15Z
Fecha de publicación2022-01-01
ResumenThis paper tackles the problem of forecasting real-life crime. However, the recollected data only produced thirty-five short-sized crime time series for three urban areas. We present a comparative analysis of four simple and four machine-learning-based ensemble forecasting methods. Additionally, we propose five forecasting techniques that manage the seasonal component of the time series. Furthermore, we used the symmetric mean average percentage error and a Friedman test to compare the performance of the forecasting methods and proposed techniques. The results showed that simple moving average with seasonal removal techniques produce the best performance for these series. It is important to highlight that a high percentage of the time series has no auto-correlation and a high level of symmetry, which is deemed as white noise and, therefore, difficult to forecast.es_ES
Doihttps://doi.org/10.3390/sym14061231es_ES
URIhttps://riuat.uat.edu.mx/handle/123456789/2216
Idiomaeses_ES
EditorialMDPI AGes_ES
RelaciónSymmetryes_ES
URL relacionadohttps://doi.org/10.3390/sym14061231es_ES
DerechosAcceso abierto (Metadatos de producción científica)es_ES
Licenciahttp://purl.org/coar/access_right/c_abf2es_ES
FuenteSymmetry
TítuloShort Time Series Forecasting: Recommended Methods and Techniqueses_ES
TipoArtículoes_ES
ArbitradoHa sido Arbitradoes_ES
AutorCruz-Nájera, Mariel Abigail
AutorTreviño-Berrones, Mayra Guadalupe
AutorPonce-Flores, Mirna Patricia
AutorTerán-Villanueva, Jesús David
AutorCastán-Rocha, José Antonio
AutorIbarra-Martínez, Salvador
AutorSantiago, Alejandro
AutorLaria-Menchaca, Julio
AutorCruz-Nájera, Mariel Abigailes_ES
AutorTreviño-Berrones, Mayra Guadalupees_ES
AutorPonce-Flores, Mirna Patriciaes_ES
AutorTerán-Villanueva, Jesús Davides_ES
AutorCastán-Rocha, José Antonioes_ES
AutorIbarra-Martínez, Salvadores_ES
AutorSantiago, Alejandroes_ES
AutorLaria-Menchaca, Julioes_ES
InstituciónUniversidad Autónoma de Tamaulipas
InstituciónUniversidad Autónoma de Tamaulipases_ES
Número6es_ES
Rango de páginas1231es_ES
URL relacionadahttps://doi.org/10.3390/sym14061231
Tipo de artículoIndexado
Tipo de artículoIndexadoes_ES
Volumen14es_ES

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