Прегледај по Аутор "Brtka, Eleonora"

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    Method PPC for Precise Piecewise Correlation after Histogram Segmentation
    (MDPI, 2024) Ognjenovic, Visnja; Stojanov, Jelena; Brtka, Vladimir; Blazic, Marko; Brtka, Eleonora; Berkovic, Ivana
    Correlation, functioning as a symmetric relation, is very powerful indicator of the mutual association between two attributes. The problem of weak correlation indicates a lack of linearity in the observed range. This paper presents the precise piecewise correlation method, which overcomes the problem by determining the segments where the linear association will be present. The determination was achieved using the histogram segmentation method. The conditions of the application and analysis of the method are presented, as well as the application of the method to the representative datasets. The obtained results confirm the existence of stronger linear associations on the segments. Detected correlations reveal the strength and nature of the symmetric association between two attributes on each of the separated segments.
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    Model of Hybrid Electric Vehicle with Two Energy Sources
    (MDPI, 2022) Brtka, Eleonora; Jotanović, Gordana; Stjepanović, Aleksandar; Jausevac, Goran; Kosovac, Amel; Cvitić, Ivan; Kostadinović, Miroslav
    The paper proposes a Hybrid Electric Vehicle (HEV) design based on the installation of a fuel cell (FC) module in the existing Daewoo Tico electric vehicle to increase its range in urban areas. Installing an FC module supplied by a 2 kg hydrogen tank would not significantly increase the mass of the electric vehicle, and the charging time of the hydrogen tank is lower than the battery charging time. For design analysis, a model was created in the MATLAB/Simulink software package. The model simulates vehicle range at different HEV speeds for Absorbent Glass Mat (AGM) and Proton Exchange Membrane Fuel Cell (PEMFC) power sources. The greatest anticipated benefit derived from the model analysis relates to velocities ranging from 20 km/h to 30 km/h, although the optimal HEV velocity in an urban area is in the range of 30 km/h to 40 km/h. The results indicate that this conversion of Electric Vehicle (EV) to HEV would bring a benefit of 87.4% in terms of vehicle range in urban areas. Therefore, the result of the conversion in this case is a vehicle with sub-optimal characteristics, which are nevertheless very close to optimal.
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    The Cuts Selection Method Based on Histogram Segmentation and Impact on Discretization Algorithms
    (MDPI, 2022) Ognjenovic, Visnja; Brtka, Vladimir; Stojanov, Jelena; Brtka, Eleonora; Berkovic, Ivana
    The preprocessing of data is an important task in rough set theory as well as in Entropy. The discretization of data as part of the preprocessing of data is a very influential process. Is there a connection between the segmentation of the data histogram and data discretization? The authors propose a novel data segmentation technique based on a histogram with regard to the quality of a data discretization. The significance of a cut’s position has been researched on several groups of histograms. A data set reduct was observed with respect to the histogram type. Connections between the data histograms and cuts, reduct and the classification rules have been researched. The result is that the reduct attributes have a more irregular histogram than attributes out of the reduct. The following discretization algorithms were used: the entropy algorithm and the Maximal Discernibility algorithm developed in rough set theory. This article presents the Cuts Selection Method based on histogram segmentation, reduct of data and MD algorithm of discretization. An application on the selected database shows that the benefits of a selection of cuts relies on histogram segmentation. The results of the classification were compared with the results of the Naïve Bayes algorithm