Neuronal Network Artificial Model for Real Estate Appraisal: Logic, controversies, and utility for the Romanian context

Helga Flavia Tothăzan () and Adela Deaconu ()
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Helga Flavia Tothăzan: “Babes-Bolyai†University of Cluj-Napoca
Adela Deaconu: “Babes-Bolyai†University of Cluj-Napoca

Ovidius University Annals, Economic Sciences Series, 2020, vol. XX, issue 2, 1093-1100

Abstract: The requirement for statistical techniques in the appraisal process is far-reaching for every country. Market price accuracy for properties is mean in economics filed, mass appraisal, and for all users of appraisals reports. Studies were developing for econometric models that can be applied in real estate issues. Literature dominates for the USA and UK and stands a need to be tested for emerging (developing) markets. The paper aims to give some hints of the logic, the problems, benefits, and a guide of the ANN (Artificial neuronal network) technique. In the study, much practical information for ANN's representing an encouragement and a tool for other emerging countries to append the technique. We conclude that ANN is critical to be applied in property valuation for emerging countries in the global environment.

Keywords: Artificial Neural Network model; market value; appraisal; emerging countries; accuracy (search for similar items in EconPapers)
JEL-codes: L85 R30 R31 (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:ovi:oviste:v:xx:y:2020:i:2:p:1093-1100

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