Residential property valuation

2021 ◽  
pp. 81-90
Author(s):  
Damian Kininmonth
Keyword(s):  
Residential Property ◽  
Property Valuation

Residential property valuation using GIS

2015 ◽  
Author(s):  
Sharifah Norashikin Bohari ◽  
Siti Nor Maizah Saad ◽  
Faradina Marzukhi ◽  
Ashnita Rahim ◽  
Ainul Dzahira Ahmad Darim
Keyword(s):  
Residential Property ◽  
Property Valuation

scholarly journals Valuing Historical and Open Space Amenities with Hedonic Property Valuation Models

2016 ◽  
Vol 45 (1) ◽  
pp. 44-67
Author(s):  
Robert L. Hicks ◽  
Bonnie M. Queen
Keyword(s):  
Open Space ◽  
Property Values ◽  
Nonmarket Valuation ◽  
Economic Benefits ◽  
Residential Property ◽  
Revealed Preferences ◽  
Property Valuation ◽  
Historic Areas ◽  
Hedonic Property ◽  
Statistical Effects

Impacts of historic and cultural amenities on property values and the economy have not been widely studied in part because of problems isolating statistical effects using nonmarket valuation and lack of study areas. Three jurisdictions in Virginia containing major historic sites provide a unique setting in which to isolate the effects of historical amenities on residential property values using revealed preferences and quantify their economic benefits. We find that historic areas provide both open space and historic amenities. Furthermore, being adjacent to a historical area is not a positive benefit on average, perhaps because of activity and congestion associated with tourism. Residing close to such areas is valuable to buyers.

Variance in residential property valuation in Lagos, Nigeria

2011 ◽  
Vol 29 (3) ◽  
pp. 222-237 ◽  
Author(s):  
G.K. Babawale ◽  
C.A. Ajayi
Keyword(s):  
Residential Property ◽  
Property Valuation

Optimisation to ANN Inputs in Automated Property Valuation Model with Encog 3 and winGamma

2013 ◽  
Vol 462-463 ◽  
pp. 1081-1086
Author(s):  
Nguyen Vo ◽  
Hao Shi ◽  
Jakub Szajman
Keyword(s):  
Design Methodology ◽  
Tax Revenue ◽  
Residential Property ◽  
Property Valuation ◽  
Valuation Model ◽  
Property Evaluation ◽  
Residential Properties ◽  
Property Model ◽  
Artificial Neural Network Ann ◽  
Hidden Layer

An automated property model for prediction of the sales price of residential properties with optimized inputs was developed. Optimised inputs improve efficiency and speed of an Artificial Neural Network (ANN). Property appraisal ANNs have a great potential not only to save time and money but also help local government authorities to determine the tax revenue. While the criteria for the ANN’s number of hidden layer neurons are well known, there is no theory to support the optimisation to ANN inputs. The proposed optimisation to ANN inputs procedure aims to resolve some of the issues in using ANNs especially in the case of automated property valuation modelling (AVM). A brief review of ANNs and their applications is given, followed by the discussion of the ANN design methodology and optimisation. Details of ANN optimisation using Java based Encog 3 and winGamma are presented in this paper. It is shown that optimisation to ANN inputs can improve the accuracy in residential property evaluation using winGamma and Encog 3.

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