Genetic Programming Forecasting of Real Estate Prices of Residential Single Family Homes in Southern California
Created by W.Langdon from
gp-bibliography.bib Revision:1.7177
- @Article{Kaboudan:2008:JREL,
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author = "Mak Kaboudan",
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title = "Genetic Programming Forecasting of Real Estate Prices
of Residential Single Family Homes in Southern
California",
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journal = "Journal of Real Estate Literature",
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year = "2008",
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volume = "16",
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number = "2",
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pages = "217--240",
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keywords = "genetic algorithms, genetic programming",
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ISSN = "0927-7544",
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publisher = "American Real Estate Society",
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URL = "
http://aresjournals.org/doi/abs/10.5555/reli.16.2.a881465823035385",
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broken = "http://ares.metapress.com/content/a881465823035385/",
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abstract = "Use of an artificial intelligence technique, genetic
programming (GP), is introduced here to predict real
estate residential single family home prices. GP is a
computerised random search technique that can deliver
regression-like models. Spatiotemporal model
specifications of periodic average neighbourhood prices
are implemented to predict individual property prices.
Average price variations are explained in terms of
changes in home attributes, spatial attributes, and
temporal economic variables. Quarterly data (2000-2005)
from two cities in Southern California are used to
obtain GP and standard statistical models (generalised
least square - GLS). Results obtained suggest that
forecasts from city neighborhood average price GP
equations may have advantage over forecasts from GLS
equations and over forecasts from models estimated
using city aggregated data.",
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notes = "house price prediction in US of america
http://business.fullerton.edu/finance/jrel/",
- }
Genetic Programming entries for
Mahmoud A Kaboudan
Citations