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The algorithm of a clustering of fund of the residential real-estate is based on a neural network simulation using T. Kokhonnen’s maps. Self-organizing maps (SOM) divide 296 objects into 16 clusters based on 33 signs. An important result of the research is the possibility of structural analysis of housing stock which allows to form an idea of his general condition. During periodic inspection and analysis of the condition of housing stock relocation of an object in other cluster will specify the changed technical condition. The quantitative composition of similar clusters will allow to determine the necessary volume of investment of these activities

Kohonen cards for clustering fund of the residential real-estate