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Daily Calls Volume Forecasting
Dalarna University, School of Technology and Business Studies, Statistics.
Dalarna University, School of Technology and Business Studies, Statistics.
2010 (English)Independent thesis Advanced level (degree of Master (Two Years))Student thesis
Abstract [en]

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.

Place, publisher, year, edition, pages
Börlange, Dalarna, 2010. , 35 p.
Keyword [en]
Rescue 1122, Time series forecasting, daily call volume, ARIMA Modeling
Identifiers
URN: urn:nbn:se:du-4852OAI: oai:dalea.du.se:4852DiVA: diva2:518902
Uppsok
Social and Behavioural Science, Law
Supervisors
Available from: 2010-06-21 Created: 2010-06-21 Last updated: 2012-04-24Bibliographically approved

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf