A Neural Network Technique for Detecting and Modelling Residential Property Sub-Markets

1998 ◽  
pp. 424-427
Author(s):  
O. M. Lewis ◽  
J. A. Ware ◽  
D. Jenkins
Keyword(s):  
Neural Network ◽  
Residential Property

International Real Estate Review

2004 ◽  
Vol 7 (1) ◽  
pp. 121-138
Author(s):  
Xin J. Ge ◽  
◽  
G. Runeson ◽  
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Hong Kong ◽  
Time Series Data ◽  
Series Data ◽  
Residential Property ◽  
Neural Network Approach ◽  
Price Performance ◽  
The Neural Network ◽  
Property Price

This paper develops a forecasting model of residential property prices for Hong Kong using an artificial neural network approach. Quarterly time-series data are applied for testing and the empirical results suggest that property price index, lagged one period, rental index, and the number of agreements for sales and purchases of units are the major determinants of the residential property price performance in Hong Kong. The results also suggest that the neural network methodology has the ability to learn, generalize, and converge time series.

A novel neural network technique for the valuation of residential property

1997 ◽  
Vol 5 (4) ◽  
pp. 224-229 ◽  
Author(s):  
O. M. Lewis ◽  
J. A. Ware ◽  
D. Jenkins
Keyword(s):  
Neural Network ◽  
Residential Property

Residential Property Price Prediction with FNN Network Model

2011 ◽  
Vol 271-273 ◽  
pp. 1638-1643
Author(s):  
Zhang Xiaoli
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Fuzzy Neural Network ◽  
Market Price ◽  
Residential Property ◽  
Property Market ◽  
Price Prediction ◽  
Fuzzy Neural ◽  
Neural Network Prediction ◽  
Network Prediction

In order to predict the new residential property market price, a Fuzzy Neural Network (FNN) prediction model was proposed. It was used to estimate the appropriate price level for a new property by learning from historical data on the correlations between various factors that influence the prices of properties and the actual selling prices. In particular, an artificial neural network prediction model was developed to compare it accuracy with the fuzzy neural network prediction model. The experimental results show that the fuzzy neural network prediction model has strong function approximation ability and is suitable for residential properties price prediction depending on the quality of the available data.

Autofluorescence spectroscopy of oral leukoplakia using an artificial neural network

2000 ◽  
Vol 25 (4) ◽  
pp. 325-325
Author(s):  
J.L.N. Roodenburg ◽  
H.J. Van Staveren ◽  
N.L.P. Van Veen ◽  
O.C. Speelman ◽  
J.M. Nauta ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Oral Leukoplakia ◽  
Autofluorescence Spectroscopy ◽  
Artificial Neural
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