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Artificial Intelligence Review

, Volume 49, Issue 3, pp 393–405 | Cite as

Enhancement of parcel valuation with adaptive artificial neural network modeling

  • Şükran Yalpır
Article
  • 240 Downloads

Abstract

This study targets a research on the application of artificial neural network (ANN) and multiple regression analysis (MRA) approaches in Geomatics Engineering science to land valuation process. The prediction capability was investigated and evaluated using three ANN models constructed with different activation functions (sigmoid, tangent hyperbolic and adaptive activation function) and MRA was used as a reference approach. These four methodologies were applied to land valuation in order to model the unit market value with various inputs based on essential criteria. All approaches were investigated with their estimation level in training and testing data. It was observed that adaptive ANN performed noticeably higher predicting the values with the highest accuracy and giving the smallest RMSE value in validation process, although other methodologies approximated to the raw data at a promising level for further valuation-based applications.

Keywords

Real estate valuation Artificial neural network (ANN) Adaptive ANN 

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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Geomatics Engineering DepartmentSelcuk UniversityKonyaTurkey

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