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Representative Residential Property Model—Soft Computing Solution

Author

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  • Aneta Chmielewska

    (Institute of Spatial Management and Geography, Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland)

  • Małgorzata Renigier-Biłozor

    (Institute of Spatial Management and Geography, Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland)

  • Artur Janowski

    (Institute of Geodesy and Civil Engineering, Faculty of Geoengineering, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland)

Abstract

Residential properties are a major component of the environment and economy and a key element for the quality of human life. Faced with disruptive ideological and technological changes in the world, real estate analysis has also become a key research problem for many academic centers and private institutions. Due to the complex nature of properties, they are one of the most difficult and troublesome subjects of analysis. Given the rapid advancements in competitive automated analytical models, the problem of data representative sample selection may prove to be a very wide-reaching subject. The aim of this paper was the assessment of the particular soft computing methods’ (e.g., Self-Organizing Maps, Rough Set Theory) usefulness for selecting a representative property model. The obtained results confirm that the use of these methods leads to the creation of a model that enables a more reality-based view of the uncertainty and imprecise residential environment.

Suggested Citation

  • Aneta Chmielewska & Małgorzata Renigier-Biłozor & Artur Janowski, 2022. "Representative Residential Property Model—Soft Computing Solution," IJERPH, MDPI, vol. 19(22), pages 1-24, November.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:22:p:15114-:d:974590
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