Advanced
search

To read this content please select one of the options below:

Neural networks: the prediction of residential values

Stanley McGreal (Reader and Director, Centre for Research on Property and Planning at the School of the Built Environment, University of Ulster, Northern Ireland)
Alastair Adair (Chair of property investment and head of the School of the Built Environment, University of Ulster, Northern Ireland)
Dylan McBurney (Research assistant in the School of the Built Environment, University of Ulster, Northern Ireland)
David Patterson (Research officer in the Northern Ireland Knowledge Engineering Laboratory, University of Ulster, Northern Ireland)

Journal of Property Valuation and Investment

ISSN: 0960-2712

Article publication date: 1 March 1998

1943

Abstract

The potential application of data mining techniques in the extraction of information from property data sets is discussed. Particular interest is focused upon neural networks in the valuation of residential property with an evaluation of their ability to predict. Model testing infers a wide variation in the range of outputs with best results for stratified market subsets, using postal code as a locational delimiter. The paper questions whether predicted outcomes are within the range of valuation acceptability and examines issues relating to potential biasing and repeatability of results.

Keywords

Citation

McGreal, S., Adair, A., McBurney, D. and Patterson, D. (1998), "Neural networks: the prediction of residential values", Journal of Property Valuation and Investment, Vol. 16 No. 1, pp. 57-70. https://doi.org/10.1108/14635789810205128

Publisher

:

MCB UP Ltd

Copyright © 1998, MCB UP Limited

Related articles

Manage cookies

We’re listening — tell us what you think

Join us on our journey