Review on the Application of Artificial Neural Networks in Real Estate Valuation

Abstract

Real estate appraisal is needed in assessment of the value of properties and contribute the regional economy of any country. Real estate valuation is thus an important subject, which has to be studied carefully as there are many individual subjective criteria, which often results in variations, which makes the traditional valuation methods to be inadequate. This work aimed at coping with the complexity of real estate valuation, by putting forth the advantages of artificial neural network, one of the novel model of real estate appraisal. The review of literature has helped to establish that the neural network model is better than the traditional model previously. This work opens up a new and better understanding to the principle of real estate evaluation.

The role of neural network for estimating real estate prices value in post COVID-19: a case of the middle east market

“…However, Kok et al [11] argued that the effectiveness of combined manual and automated models was higher than individual models. For instance, a review [3] showed that some of these models that successfully combined artificial neural networks and regression analysis included particle swarm optimization algorithm, support vector machine (SVM), and decision tree. In this respect, neural networks can be integrated with other real estate valuation models for precise estimates.…”

“…On that note, the main objective of this research is to propose and demonstrate the use of neural network models in estimating real estate prices in the Middle East. Specifically, neural networks in computerization are artificial networks inspired uniquely by the biological nervous system thus mimicking the functionality of the human brain and neurons [3]. For this study, the underlying goal is to use artificial neural networks (ANN) to estimate real estate prices in the Middle East for an accurate valuation.…”

Predicting Highest Professional Qualification Applying the Usage of Strategic Management Tools and Techniques and Years of Professional Experience

“…Data models efficiently classify attributes and improve precision in appraisal and real estate market value prediction. Examples are the use of neural networks and genetic algorithms in real estate valuation [24][25][26]. Boosted regression tree was applied in [27].…”

A real estate valuation model using boosted feature selection

“…An ANN is considered to be a powerful data modeling tool based on its ability to represent nonlinear problems and thus allow a broader range of variation. These models can capture different quantitative and qualitative variables that affect the value of the given data ( [4], [5]). This means that in the field of real estate valuation, this capability can be very useful in complex systems found in this field where motivations, tastes and budget availability often do not follow rational behaviors.…”

“…This means that in the field of real estate valuation, this capability can be very useful in complex systems found in this field where motivations, tastes and budget availability often do not follow rational behaviors. The ANN has demonstrated its robustness as a real estate valuation model comparing to the hedonic models in many cases( [5], [6], [7], [8], [9]). Moreover, due to its theory of universal approximation, the ANN is capable of fitting any continuous function, allowing them to capture complex trends, and working with extrapolated data [10].…”