Assessing the Rental Value of Residential Properties: An Abductive Learning Networks Approach

J. OF REAL ESTATE RESEARCH, Vol. 12 No. 1

Posted: 4 Jul 1997

See all articles by Kee S. Kim

Kee S. Kim

Missouri State University - Department of Finance and General Business

Walt A. Nelson

Missouri State University - Department of Finance and General Business

Abstract

This paper attempts to estimate rental value of residential properties using Abductive Learning Networks (ALN), an 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.

JEL Classification: R32

Suggested Citation

Kim, Kee S. and Nelson, Walt A., Assessing the Rental Value of Residential Properties: An Abductive Learning Networks Approach. J. OF REAL ESTATE RESEARCH, Vol. 12 No. 1. Available at SSRN: https://ssrn.com/abstract=9288

Kee S. Kim (Contact Author)

Missouri State University - Department of Finance and General Business ( email )

United States
417-836-6345 (Phone)

Walt A. Nelson

Missouri State University - Department of Finance and General Business ( email )

United States

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