Yayın:
GIS & Machine Learning based Mass Appraisal of Residential Properties in England & Wales

dc.contributor.authorMete, Muhammed Oguzhan
dc.contributor.authorYomralioglu, Tahsin
dc.date.accessioned2026-01-24T22:37:15Z
dc.date.issued2022-04-03
dc.description.abstractProperty value is needed in many transactions such as purchase and sale, taxation, expropriation, capital market activities. Geographic Information Systems (GIS) and Machine Learning methods are widely used in automated mass appraisal practices. Analysing the Machine Learning based mass appraisal applications, it is seen that locational criteria are insufficiently used during the price prediction process. Whereas, locational criteria like proximity to important places, sea or green areas views, smooth topography are some of the spatial factors that extremely affect the property value. In this study, a hybrid approach is developed by integrating GIS and Machine Learning for mass appraisal of residential properties in England and Wales.
dc.description.urihttps://dx.doi.org/10.5281/zenodo.6410120
dc.description.urihttps://dx.doi.org/10.5281/zenodo.6410119
dc.identifier.doi10.5281/zenodo.6410120
dc.identifier.openairedoi_dedup___::2e614058778da0031510be076506c1aa
dc.identifier.urihttps://hdl.handle.net/11527/38687
dc.publisherZenodo
dc.rightsOPEN
dc.sdg.typeGoal 11: Sustainable Cities and Communities
dc.titleGIS & Machine Learning based Mass Appraisal of Residential Properties in England & Wales
dc.typeArticle
dspace.entity.typePublication

Dosyalar

Koleksiyonlar