Artificial neural networks and geostatistical models for housing valuations in urban residential areas

@inproceedings{Balsera2018ArtificialNN,
  title={Artificial neural networks and geostatistical models for housing valuations in urban residential areas},
  author={M. Carmen Morillo Balsera and Sandra Mart{\'i}nez-Cuevas and I{\~n}igo Molina S{\'a}nchez and C{\'e}sar Garc{\'i}a-Aranda and M. Estibaliz Martinez Izquierdo},
  year={2018}
}
ABSTRACTProperty valuation studies often use classical statistics techniques. Among these techniques, the Artificial Neural Networks are the most applied, overcoming the inflexibility and the linearity of the hedonic models. Other researchers have used Geostatistics techniques, specifically the Kriging Method, for interpreting spatial-temporal variability and to predict housing unit prices. The innovation of this study is to highlight how the Kriging Method can help to better understand the… CONTINUE READING