Assessing the Rental Value of Residential Properties: An Abductive Learning Networks Approach
AbstractThis paper attempts to estimate rental value of residential properties using Abductive Learning Networks (ALN), and artificial intelligence technique. The results indicate that the ALN model provides an accurate estimation of rents with only seven input variables, while other multivariate statistical techniques do not. The ALN model automatically selects the best network structure, node types and coefficients, and therefore it simplifies the maintenance of the model. Once the final model is synthesized, the ALN model becomes very compact, rapidly executable and cost-effective.
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Bibliographic InfoArticle provided by American Real Estate Society in its journal Journal of Real Estate Research.
Volume (Year): 12 (1996)
Issue (Month): 1 ()
Contact details of provider:
Postal: American Real Estate Society Clemson University School of Business & Behavioral Science Department of Finance 401 Sirrine Hall Clemson, SC 29634-1323
Web page: http://www.aresnet.org/
Postal: Diane Quarles American Real Estate Society Manager of Member Services Clemson University Box 341323 Clemson, SC 29634-1323
Find related papers by JEL classification:
- L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services
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- Smith, Lawrence B & Rosen, Kenneth T & Fallis, George, 1988. "Recent Developments in Economic Models of Housing Markets," Journal of Economic Literature, American Economic Association, vol. 26(1), pages 29-64, March.
- Karl L. Guntermann & Stefan Norrbin, 1987. "Explaining the Variability of Apartment Rents," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 15(4), pages 321-340.
- William B. Shear, 1983. "A Note on Occupancy Turnover in Rental Housing Units," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 11(4), pages 525-538.
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