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Pregled bibliografske jedinice broj: 1033117

Location Intelligence in Cogenerated Heating Potential Data Analysis


Karabegović, Almir; Ponjavić, Mirza; Duić, Neven; Novosel; Tomislav
Location Intelligence in Cogenerated Heating Potential Data Analysis // Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, FedCSIS 2019
Leipzig, Njemačka, 2019. str. 613-620 doi:10.15439/2019F77 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 1033117 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Location Intelligence in Cogenerated Heating Potential Data Analysis

Autori
Karabegović, Almir ; Ponjavić, Mirza ; Duić, Neven ; Novosel ; Tomislav

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, FedCSIS 2019 / - , 2019, 613-620

Skup
2019 Federated Conference on Computer Science and Information Systems (FedCSIS 2019)

Mjesto i datum
Leipzig, Njemačka, 01.09.2019. - 04.09.2019

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Cogenerated heating ; Cogenerated cooling ; Potential data analysis ; location intelligence ;

Sažetak
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

Izvorni jezik
Engleski

Znanstvena područja
Strojarstvo



POVEZANOST RADA


Projekti:
120-1201918-1920 - Racionalno skladištenje energije za održivi razvoj energetike (Duić, Neven, MZOS ) ( CroRIS)

Ustanove:
Fakultet strojarstva i brodogradnje, Zagreb

Profili:

Avatar Url Neven Duić (autor)

Poveznice na cjeloviti tekst rada:

doi ieeexplore.ieee.org

Citiraj ovu publikaciju:

Karabegović, Almir; Ponjavić, Mirza; Duić, Neven; Novosel; Tomislav
Location Intelligence in Cogenerated Heating Potential Data Analysis // Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, FedCSIS 2019
Leipzig, Njemačka, 2019. str. 613-620 doi:10.15439/2019F77 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Karabegović, A., Ponjavić, M., Duić, N., Novosel & Tomislav (2019) Location Intelligence in Cogenerated Heating Potential Data Analysis. U: Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, FedCSIS 2019 doi:10.15439/2019F77.
@article{article, author = {Karabegovi\'{c}, Almir and Ponjavi\'{c}, Mirza and Dui\'{c}, Neven}, year = {2019}, pages = {613-620}, DOI = {10.15439/2019F77}, keywords = {Cogenerated heating, Cogenerated cooling, Potential data analysis, location intelligence, }, doi = {10.15439/2019F77}, title = {Location Intelligence in Cogenerated Heating Potential Data Analysis}, keyword = {Cogenerated heating, Cogenerated cooling, Potential data analysis, location intelligence, }, publisherplace = {Leipzig, Njema\v{c}ka} }
@article{article, author = {Karabegovi\'{c}, Almir and Ponjavi\'{c}, Mirza and Dui\'{c}, Neven}, year = {2019}, pages = {613-620}, DOI = {10.15439/2019F77}, keywords = {Cogenerated heating, Cogenerated cooling, Potential data analysis, location intelligence, }, doi = {10.15439/2019F77}, title = {Location Intelligence in Cogenerated Heating Potential Data Analysis}, keyword = {Cogenerated heating, Cogenerated cooling, Potential data analysis, location intelligence, }, publisherplace = {Leipzig, Njema\v{c}ka} }

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