In the mass appraisal of properties, Machine Learning (ML) algorithms have produced
effective and promising results. Analysts use various algorithms to train their models with …

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 …

Hybrid systems as the next generation of intelligent applications within the field of mass
appraisal and valuation are investigated. Motivated by the obvious limitations of paradigms …

Determinants of house prices in Turkey are examined in this paper using the 2004
Household Budget Survey Data. In property valuation and housing market research, the …

The advancement of computational software within the last decade has facilitated enhanced
uptake of mass appraisal methodologies by the valuation and prediction accuracy in …

The aim of this paper is to compare various real estate valuation models and the manner in
which they take into account environmental variables. The reference model is taken to be a …

Inaccuracies in property valuation is a global problem. This could be attributed to the
adoption of valuation approaches, with the hedonic pricing model (HPM) being an example …

This study extended the use of artificial neural networks (ANNs) training algorithms in mass
appraisal. The goal was to verify the comparative performance of ANNs with linear, semi-log …

Purpose In the literature there are numerous tests that compare the accuracy of automated
valuation models (AVMs). These models first train themselves with price data and property …

This paper develops an artificial intelligence based automated valuation model (AI-AVM)
using the boosting tree ensemble technique to predict housing prices in Singapore. We use …