Les Inscriptions à la Bibliothèque sont ouvertes en
ligne via le site: https://biblio.enp.edu.dz
Les Réinscriptions se font à :
• La Bibliothèque Annexe pour les étudiants en
2ème Année CPST
• La Bibliothèque Centrale pour les étudiants en Spécialités
A partir de cette page vous pouvez :
Retourner au premier écran avec les recherches... |
Détail de l'auteur
Auteur J. W. Gillard
Documents disponibles écrits par cet auteur
Affiner la recherchePredicting ambulance demand using singular spectrum analysis / J. L. Vile in Journal of the operational research society (JORS), Vol. 63 N° 11 (Novembre 2012)
[article]
in Journal of the operational research society (JORS) > Vol. 63 N° 11 (Novembre 2012) . - pp. 1556–1565
Titre : Predicting ambulance demand using singular spectrum analysis Type de document : texte imprimé Auteurs : J. L. Vile, Auteur ; J. W. Gillard, Auteur ; P. R. Harper, Auteur Année de publication : 2012 Article en page(s) : pp. 1556–1565 Note générale : operational research Langues : Anglais (eng) Mots-clés : health service; emergency medical services; forecasting; singular spectrum analysis Index. décimale : 001.424 Résumé : This paper demonstrates techniques to generate accurate predictions of demand exerted upon the Emergency Medical Services (EMS) using data provided by the Welsh Ambulance Service Trust (WAST). The aim is to explore new methods to produce accurate forecasts that can be subsequently embedded into current OR methodologies to optimise resource allocation of vehicles and staff, and allow rapid response to potentially life-threatening emergencies. Our analysis explores a relatively new non-parametric technique for time series analysis known as Singular Spectrum Analysis (SSA). We explain the theory of SSA and evaluate the performance of this approach by comparing the results with those produced by conventional time series methods. We show that in addition to being more flexible in approach, SSA produces superior longer-term forecasts (which are especially helpful for EMS planning), and comparable shorter-term forecasts to well established methods. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v63/n11/abs/jors2011160a.html [article] Predicting ambulance demand using singular spectrum analysis [texte imprimé] / J. L. Vile, Auteur ; J. W. Gillard, Auteur ; P. R. Harper, Auteur . - 2012 . - pp. 1556–1565.
operational research
Langues : Anglais (eng)
in Journal of the operational research society (JORS) > Vol. 63 N° 11 (Novembre 2012) . - pp. 1556–1565
Mots-clés : health service; emergency medical services; forecasting; singular spectrum analysis Index. décimale : 001.424 Résumé : This paper demonstrates techniques to generate accurate predictions of demand exerted upon the Emergency Medical Services (EMS) using data provided by the Welsh Ambulance Service Trust (WAST). The aim is to explore new methods to produce accurate forecasts that can be subsequently embedded into current OR methodologies to optimise resource allocation of vehicles and staff, and allow rapid response to potentially life-threatening emergencies. Our analysis explores a relatively new non-parametric technique for time series analysis known as Singular Spectrum Analysis (SSA). We explain the theory of SSA and evaluate the performance of this approach by comparing the results with those produced by conventional time series methods. We show that in addition to being more flexible in approach, SSA produces superior longer-term forecasts (which are especially helpful for EMS planning), and comparable shorter-term forecasts to well established methods. DEWEY : 001.424 ISSN : 0160-5682 En ligne : http://www.palgrave-journals.com/jors/journal/v63/n11/abs/jors2011160a.html