Daily Calls Volume Forecasting


Autoria(s): AJMAL, KHAN; TAHIR MAHMOOD, HASHMI
Data(s)

2010

Resumo

A massive amount has been written about forecasting but few articles are written about the development of time series models of call volumes for emergency services. In this study, we use different techniques for forecasting and make the comparison of the techniques for the call volume of the emergency service Rescue 1122 Lahore, Pakistan. For the purpose of this study data is taken from emergency calls of Rescue 1122 from 1st January 2008 to 31 December 2009 and 731 observations are used. Our goal is to develop a simple model that could be used for forecasting the daily call volume. Two different approaches are used for forecasting the daily call volume Box and Jenkins (ARIMA) methodology and Smoothing methodology. We generate the models for forecasting of call volume and present a comparison of the two different techniques.

Formato

application/pdf

Identificador

http://urn.kb.se/resolve?urn=urn:nbn:se:du-4852

Idioma(s)

eng

Publicador

Högskolan Dalarna, Statistik

Högskolan Dalarna, Statistik

Börlange, Dalarna

Direitos

info:eu-repo/semantics/openAccess

Palavras-Chave #Rescue 1122 #Time series forecasting #daily call volume #ARIMA Modeling
Tipo

Student thesis

info:eu-repo/semantics/bachelorThesis

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