2017
DOI: 10.1108/pm-06-2016-0027
|View full text |Cite
|
Sign up to set email alerts
|

Artificial neural network in property valuation: application framework and research trend

Abstract: Purpose The predictive accuracy and reliability of artificial intelligence models, such as the artificial neural network (ANN), has led to its application in property valuation studies. However, a large percentage of such previous studies have focused on the property markets in developed economies, and at the same time, effort has not been put into documenting its research trend in the real estate domain. The purpose of this paper is to critically review the studies that adopted ANN for property valuation in o… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

1
39
0
1

Year Published

2018
2018
2024
2024

Publication Types

Select...
9

Relationship

1
8

Authors

Journals

citations
Cited by 46 publications
(47 citation statements)
references
References 68 publications
1
39
0
1
Order By: Relevance
“…This has resulted in a number of studies conducted in different property markets around the world that have compared the predictive accuracy of HPM and the ANN technique (McGreal et al, 1998). (Abidoye and Chan, 2017) reported that most of these studies emanated from developed countries, they were conducted by university scholars, and that the findings of these studies were mixed. However, in most cases, the ANN technique outperformed the HPM approach in terms of predictive accuracy.…”
Section: Literature Reviewmentioning
confidence: 99%
See 1 more Smart Citation
“…This has resulted in a number of studies conducted in different property markets around the world that have compared the predictive accuracy of HPM and the ANN technique (McGreal et al, 1998). (Abidoye and Chan, 2017) reported that most of these studies emanated from developed countries, they were conducted by university scholars, and that the findings of these studies were mixed. However, in most cases, the ANN technique outperformed the HPM approach in terms of predictive accuracy.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In the present study, the number of neurons in the hidden layer was automatically determined by the R programming software, by optimizing the network architecture that best fit the data during the grid search, using the default parameters in terms of learning rate, stopping criteria and weight decay. A detailed process of the application of the ANN technique in property valuation can be found in Abidoye and Chan (2017). Table 2 shows the details of the ANN model developed in this study.…”
Section: Model Specification: Artificial Neural Networkmentioning
confidence: 99%
“…Much of the work in this area is concerned with predicting the sales price of properties. Abidoye and Chan [37] provide a review of the applications of one form of MLAs, artificial neural networks, finding most studies using sales data with just two concerned with rental values. So, whilst Schernthanner, Asche [20] state that “no study has been found estimating rental prices via machine learning methods ”, some studies do exist.…”
Section: Introductionmentioning
confidence: 99%
“…The ANN performs well for modeling the non-linear relationship because of its characteristics of semi-parametric regression. In addition to the basic MRA, although researchers have to face the "black box" of the ANN's structure, it is still the most popular model used in AI-based models [36][37][38][39][40][41][42][43][44][45][46][47][48][49].…”
Section: Artificial Neural Network (Ann)mentioning
confidence: 99%