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Annals of Computer Science and Information Systems, Volume 18

Proceedings of the 2019 Federated Conference on Computer Science and Information Systems

Location Intelligence in Cogenerated Heating Potential Data

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DOI: http://dx.doi.org/10.15439/2019F77

Citation: Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 18, pages 613620 ()

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Abstract. Different methodologies are used to assess the potential for using high efficiency cogeneration for cooling and heating. They are mostly adapted to the availability of data and tools for their analytical processing. This paper presents the approach applying location intelligence as a tool that allows using geospatial analysis algorithms and geovisualization of its results. Due to the extremely large amount of data and the dependence of the results on their accuracy and the level of aggregation, the initial methodology of the analytical process implied two steps: wide scale mapping by the``top down'' method, and local mapping by ``bottom up'' method. However, in order to overcome the problem of regional disparities of quality and the existence of spatial data, certain adaptations of the initial methodology have been made considering the need for a single analytical approach for the entire area of interest. Randomized control of the obtained results indicate that applied geospatial algorithms satisfy the required level of accuracy and reliability of the final methodology.

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