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Please use this identifier to cite or link to this item: http://hdl.handle.net/10204/1342

Title: Model for election night forecasting applied to the 2004 South African elections
Authors: Greben, JM
Elphinstone, E
Holloway, J
Keywords: Clustering
Forecasting
Elections
Issue Date: Jun-2006
Publisher: ORSSA - Operations Research Society of South Africa
Citation: Greben. JM, Elphinstone, E and Holloway, J. 2006. Model for election night forecasting applied to the 2004 South African elections. Orion: The Journal of ORSSA, Vol. 22(1), pp 1-22
Abstract: A novel model has been developed to predict elections on the basis of early results. The electorate is clustered according to their behaviour in previous elections. Early results in the new elections can then be translated into voter behaviour per cluster and extrapolated over the whole electorate. This procedure is of particular value in the South African elections which tend to be highly biased, as early results do not give a proper representation of the overall electorate. In this paper the authors explain the methodology used to obtain the predictions. In particular, they look at the different clustering techniques that can be used, such as k-means, fuzzy clustering and k-means in combination with discriminate analysis. The authors assess the power of the different approaches by comparing their convergence towards the final results.
Description: Copyright: 2006 ORSSA
URI: http://hdl.handle.net/10204/1342
ISSN: 0529-191X
Appears in Collections:Infrastructure engineering
General science, engineering & technology

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