The use of urban indicators in forecasting a real estate value with the use of deep neural network
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Faculty of Civil Engineering, Architecture and Environmental Engineering, University of Zielona Góra, 1 Prof. Z. Szafrana street, 65-516, Zielona Góra, Poland
Department of Computational Intelligence, Faculty of Physics, Mathematics and Computer Science, Cracow University of Technology, 24 Warszawska street, 31-155, Cracow, Poland
Submission date: 2018-08-27
Acceptance date: 2018-12-05
Online publication date: 2018-12-31
Publication date: 2018-12-01
Reports on Geodesy and Geoinformatics 2018;106:25–34
Records of municipal planning documents directly affect the land use. In this way, the market price of the land is also shaped. Awareness of the economic and social consequences of adapting specific solutions is the primary argument that should condition the local policy in terms of spatial planning. The research results indicate that the network trained with attributes which do not describe a property value by its price was able to estimate it with acceptable and satisfactory results. The possibility to use artificial multilayer networks in spatial policy decision-making seems well founded. The research results show the relevance of the assumption that using them for modeling can be helpful in selecting the most advantageous variant of planning arrangements in a local law document which determines the land use and development, therefore impacts its value.
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