An Exploration of Neural Networks and Its Application to Real Estate Valuation
This research applies neural network (NN) technology to real estate appraisal and compares the performance of two NN models in estimating the sales price of residential properties with a traditional multiple regression model. The study is based on 288 sales of homes in Fort Collins, Colorado. Results do not support previous findings that NNs are a superior tool for appraisal analysis. Furthermore, significant problems were encountered with the NN models: inconsistent results between packages, inconsistent results between runs of the same package, and long run times. Any appraiser who plans on using this new technology would do so with caution.
Volume (Year): 10 (1995)
Issue (Month): 2 ()
|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/
|Order Information:|| Postal: Diane Quarles American Real Estate Society Manager of Member Services Clemson University Box 341323 Clemson, SC 29634-1323|
Web: http://pages.jh.edu/jrer/about/get.htm Email:
When requesting a correction, please mention this item's handle: RePEc:jre:issued:v:10:n:2:1995:p:185-202. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (JRER Graduate Assistant/Webmaster)
If references are entirely missing, you can add them using this form.