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- W2903923218 abstract "Solar energy supplies pure environmental-friendly and limitless energy resource for human. Although the cost of solar panels has declined rapidly, technology gaps still exist for achieving cost-effective scalable deployment combined with storage technologies to provide reliable, dispatchable energy. However, it is difficult to analyze a solar data, in which data was added in every 10 min by the sensors in a short time. These data can be analyzed easier and faster with the help of data visualization. One of the popular data visualization methods for displaying massive quantity of data is parallel coordinates plot (PCP). The problem when using this method is this abundance of data can cause the polylines to overlap on each other and clutter the visualization. Thus, it is difficult to comprehend the relationship that exists between the parameters of solar data such as power rate produced by solar panel, duration of daylight in a day, and surrounding temperature. Furthermore, the density of overlapped data also cannot be determined. The solution is to implement clutter-reduction technique to parallel coordinate plot. Even though there are various clutter-reduction techniques available for visualization, they are not suitable for every situation of visualization. Thus this research studies a wide range of clutter-reduction techniques that has been implemented in visualization, identifies the common features available in clutter-reduction technique, produces a conceptual framework of clutter-reduction technique as well as proposes the suitable features to be added in parallel coordinates plot of solar energy data to reduce visual clutter." @default.
- W2903923218 created "2018-12-22" @default.
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- W2903923218 date "2018-12-11" @default.
- W2903923218 modified "2023-09-25" @default.
- W2903923218 title "Clutter-Reduction Technique of Parallel Coordinates Plot for Photovoltaic Solar Data" @default.
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- W2903923218 doi "https://doi.org/10.1007/978-981-13-3441-2_26" @default.
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